Training - Science topic

I have a numeric dependent variable (drug reports in schools) with three binary categorical predictors - whether schools receive drug training, whether schools receive discipline training, and whether schools have a high or low number of intervention practices. I have made all of these factor variables, and I am now struggling to test the assumptions of my regression analysis. Why is the scatterplot showing vertical lines? Do I need to change my Rcode? I have attatched everything below and any help would be great!

model <- lm(log_drug ~ practice_hilo + alcohol_drugabuse_f + discipline_policies_f, data = school_safety)

summary(model)

Call:

lm(formula = log_drug ~ practice_hilo + alcohol_drugabuse_f +

discipline_policies_f, data = school_safety)

Residuals:

Min 1Q Median 3Q Max

-1.864 -1.079 -0.273 1.062 4.014

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 1.37159 0.06750 20.320 <2e-16 ***

practice_hiloLow Value -0.51009 0.05397 -9.451 <2e-16 ***

alcohol_drugabuse_fYes 0.49221 0.05727 8.594 <2e-16 ***

discipline_policies_fYes -0.09211 0.06485 -1.420 0.156

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.323 on 2720 degrees of freedom

Multiple R-squared: 0.07806, Adjusted R-squared: 0.07704

F-statistic: 76.76 on 3 and 2720 DF, p-value: < 2.2e-16

I ask this question from the perspective that AI algorithms can automate tasks, analyze vast amounts of data, and suggest new research avenues. It can also improve research efficiency and speed up scientific progress, in addition to analysing massive datasets, it could identify patterns, and accelerate scientific discovery. These no doubt are advantageous benefits, but AI algorithms can also inherit biases from the data they're trained on, leading to discriminatory or misleading results, which directly affect research in terms of the quality of output. Additionally, the "black box" nature of some AI systems makes it difficult to understand how they reach conclusions, raising concerns about transparency and accountability.

Dear All,

I have an imagery with a single fish species within each image along with a list of morphometric measurements of the fish (length, width, length of tail, etc). I would like to train a CNN model that will predict these measurements having as input only the images. Any ideas what kind of architecture is ideal for this task? I read about multioutput learning, but I haven't found a practical implementation in Python.

Thank you for your time.

I would like to conduct a survey to assess the level of awareness students have regarding internet threats and their vulnerability to social engineering. However, I plan to conduct the survey twice, once before providing them with training and the second time after the training session is completed.

What are the statistical methods recommended for that? Note that the population is the same and the survey questions will be the same.

I am first time doing bacteria experiment without any prior practice. I am trying to make bifidobacterium biofilm. According to references i am incubating them in different concentration of bile acid+BL broth (2hr~24hr) and then spreading them on BL agar plate containing sheep blood.

While getting normal colonies in control plate some plate is showing white patch like the image. I am not sure if it's biofilm or just contamination. The growth condition was 5% co2, 99.9% nitrogen and 0.1% oxygen.

I scrapped some of the patch and tried to check 40x optical microscope but can not conclude anything. As i have no basic training training about bacterial experiments i am having hard time.

Thanks a lot.

I want to study the effects of train induced vibrations on nearby structures. For this purpose I used this paper :

I modeled the ballasted railway with infinite element boundary with elastic geo-material. The properties that I used are similar to the information provided in Table 1 of this paper. I simulated the wheels of the train with rigid cubes and then applied the load of each wheel on the reference point of the cube as mentioned in the paper. The steel rail is constrained at the bottom to the top surface of sleepers with the so called "Tie" constraint in the Interaction module. In addition the contact between the sleepers and the ballast is modeled using the general contact option in Abaqus (tangential behavior is assumed rough and normal behavior is the so-called Hard contact.) and finally the contact between rigid cubes (wheels) and top of the rail is modeled with the frictionless tangential behavior and Hard contact normal behavior using the individual property assignment in the general contact tab.

The problem I have is that my results don't match the results of the paper. The vertical stress in control points M1 & M3 are the same with the results of the paper however the vertical displacements in these points have a large error.

I attached my results below. What's wrong with my simulation and how can I correct my results (vertical displacement)?

I have participated in trainings whose organizers advertised on social media and during which they first presented their achievements in social media, pointed out the large income they generate within the framework of large reach in these online media, then talked about social media, marketing and online advertising used in these media, the possibility of using various applications based on artificial intelligence technology within the framework of marketing activities, creating and running advertising campaigns in social media and then presented their paid offers to gain access to these applications through created additional overlays, intermediary platforms, websites. Such training courses, webinars are usually free of charge. After the training, participants can receive free certificates confirming their participation in the training. This is a free additional form of incentive to participate in the training. On the other hand, among the forms of encouraging the purchase of access to specific AI applications is a promotional offer that lasts until the end of the training time and/or until the end of the day. however, it happens that the people conducting this type of training are not computer scientists who create AI applications, they are influencers, youtubers who have contrived to sell access to selected applications based on artificial intelligence technology, which for a certain fee will be available on created overlays, websites that act as intermediary applications to access specific source applications that are available for free on the Internet. In addition, it happens that those who conduct this kind of training do not even have a registered business and cannot even issue a VAT invoice for the services sold in this way in mediating access to selected AI applications. Surprisingly, the tax authorities in the various countries where such youtubers operate have not yet addressed this issue, given that some unethical individuals operating in this way boast about the high income they earn during such training sessions. It can be a problem of sorts for public tax authorities operating in individual countries if this kind of training and business activity is conducted via the Internet from other countries, which can be a kind of tax haven for this kind of activity. However, the problem can be serious if this kind of activity is conducted from a country referred to as a tax haven and is aimed at citizens of other countries. Apparently, there is still a lack of legal regulations that would effectively limit the use of unethical, unreliable business practices in the use of certain solutions based on artificial intelligence.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best regards,

Dariusz Prokopowicz

Who agrees, for the sake of human decency, people should be trained to use the word banal, cliché, etc. instead of the word gay? How? Why? My answer: I agree for the sake of human decency, people should be trained to use the word banal, cliché, etc. instead of the word gay. How?: Through training to obtain human empathy, human dignity, and harmony. Why?: Often the term gay is misused and the banal should be addressed with respectful terms.

I propose that seismologists in the Middle East zone join forces for peace and security for those living in all countries of the Middle East. I am ready to create a united Short-Term Forecast Network Center based on my patent.

From Israel, I cannot write separately to seismologists in some countries (you understand why). Therefore, all correspondence will initially be open in this topic. When we create an enterprise in one of the leading countries with the approval of the Ministry of Foreign Affairs, then we will decide where to organize the training Academy. First, I recommend reading book_KaY_ENG_FINAL.pdf

Could someone please provide the procedure for trained Innate Immunity?

What are the most effective techniques for mitigating overfitting in neural networks, especially when dealing with limited training data?

Are you a professional working in either Health or Education with at least 5 years post qualification experience? Do you supervise trainees in your field?

We invite you to be part of our expert panel in developing a definition of EMPATHY. Please follow this link if you would like to participate:

This inquiry is about the journal paper "Challenges facing blood transfusion services at a regional blood transfusion center in Western Kenya" written by B.M. Kavuvalu. and others. The purpose of this essay was to provide a succinct summary of the main issues with blood transfusion services in Sub-Africa.

When a model is trained using a specific dataset with limited diversity in labels, it may accurately predict labels for objects within that dataset. However, when applied to real-time recognition tasks using a webcam, the model might incorrectly predict labels for objects not present in the training data. This poses a challenge as the model's predictions may not align with the variety of objects encountered in real-world scenarios.

Are there any solutions or opinions that experts can share to guide me further in improving the model?

Thank you for considering your opinion on my problems.

In the above paper, the author states many of the O & T implied in the current AI development and market but I think two important key questions are missing:

The value of the average RMSE in my study is 0.523 for training data and 0.514 for testing. I have used 90% data for training and 10% for testing. However I am getting higher RMSE average, is this acceptable? and any study available to cite RMSE average optimum limit?

views from the above 3 and why ? What do you use out of the 3 tools or a combination of all .

Would be happy to get views

The training received by child protective services workers has gaps in transition to casework with children and families.

mental training

youth players

Clinical > book. Therefore, if a barber was trained and had a track record of successfully giving a very specific surgery then, is more likely to succeed than an MD who only has read books without clinical experience.

Hello Everyone,

Can anyone guide me to find Corpus/ Training data for readability difficulty of English texts?

Thanks in advance

Udaysimha Nerella

Looking for ways to improve collegiate athletes' vertical jump performance.

1)

I'm writing a paper review / prospective paper about the use of XR tools in the space training domain - research gaps and future applications/investigations.

There are not so many papers about the topic, expect several conference papers. So I'd like to mention XR projects ongoing from companies and I'd like to do it systematically. Do you know if there's a way to do it systematically? Like a systematic Google review?

With PRIMA, we can make a systematic literature review. So I would like to search on Google terms such as 'virtual reality space training' and nominate in the papers, the companies / projects that came out from the Google search, to provide practical examples. So I hope that I would not miss any XR company which it is currently working on the topic.

Model-centric approach to AI lead to the Transformer architecture revolution. Data-centric approach is beginning to show gains in SLM (Small Language Models) i.e. phi-x models.

There could be some gains on Compute-centric approach too, bringing training/inference time and cost down significantly. Could LLM someday be trained in minutes rather than months or days?

Hello,

For sport in general, between long traditional training and "modern" training (but not necessarily effective) which quickly seeks results sometimes at the expense of the athlete's health (strict diet, high training load, recovery time short or non-existent).

Through this "modern" method of training and sports career management, it can easily be noted that sport has "developed" very well in recent decades, in terms of new performances and new world records, but what really happens to the athlete himself, has he really developed? Doesn't he have health problems or injuries during his career or after? Is his mental or psychological state not affected by the stress generated by the demands of training and competition? Therefore, in the long term, will high-level sport not have an inverse effect on the athlete's health?

Can anyone help me with PPG signal processing? or recommend a trainer, the trainer will be paid for online training....

Creating a comprehensive mental health policy for academicians is essential to ensure the well-being and productivity of those in the academic community. Academic life can be highly demanding and stressful, leading to burnout, anxiety, and other mental health issues.

Here are some key components that should be considered when developing a mental health policy for academicians:

Implementing a mental health policy for academicians requires collaboration among various stakeholders, including administrators, faculty, staff, and students. Regular reviews and updates are essential to ensure the policy remains effective and relevant to the evolving needs of the academic community.

Given the amount of abominations that neuroscientists recite, like the dogma that we are nothing but the brain, how come part of their training/Pavlov conditioning, they are not being offered a course in at least Philosophy of Mind ? How come they don't even know what the word "consciousness" means, when it is supposed to be the very subject that they pretend to study ?

Quality improvement project and plan

I am writing a paper on employee instruction program using Augmented Reality. I am gathering information about hotels using AR to provide training to their employees for improving the performance.

List out the hotel name in India?

How effective the training is provided for betterment of the employee to perform his task to be completed in the given timeline.

Regards

Balakrishnan

Assistant Professor

Dept of Hotel Management

Bangalore

Dear collegues,

resending in case someone has missed it- I am now producing a book with Edward Elgar publishing specifically on teaching entrepreneurship in emerging markets (call attached)

It will be a guide for best practice from universities and training centres in Asia, Africa, and Latin America. I would like to share the call with you and was wondering if perhaps yourselves, any colleagues or PhD student who have taught entrepreneurship courses may be interested to kindly share their valuable experience in a short chapter or share to someone who might. Currently we have got local authors from Malaysia, Nigeria, Panama, Bahamas, Indonesia, and the UAE and look forward to more.

Apologies if it is not of interest and thank you for your time,

PM for any questions and thank you

Please no Spamming***

Hello everone.

I'm very new in ML and DL models, and i want to use CNN to train and test it on my dataset, i had very large dataset and it is already split into 80% train and 20% test.

I wrote code in python and use tensorflow to train CNN, and I'm not sure if it's correct. And now I am struggles on test CNN.

can anyone help to ensure I trained CNN corecctly and tell me how to test it? Either by giving adivices or by providing me with useful resources

I will be truly grateful.

#CNN #ML #MachineLearning #DeepLearning #ConvolutionalNeuralNetwork

How do I prepare a wisdom-based psychological spiritual training package?

I need to teach how to conduct research using internet or library sources, therefore I need to develop a successful curriculum for the proposed training on how to conduct research>

Hello,

I'm writing paper and used various optimizers to train model. I changed them during training step to get out of local minimum, and I know that people do that, but I don't know how to name that technique in the paper. Does it even have a name?

It is like simulated annealing in optimization, but instead of playing with temperature (step) we change optimizers between Adam, SDG and RMSprop. I can say for sure that it gave fantastic results.

P.S. Thank you for replies but learning rate scheduling is for leaning rate changing, optimizer scheduling is for other optimizer parameters, in general it is hyperparameter tuning. What I'm asking is about switching between optimizers, not modifying their parameters.

Thanks for support,

Andrius Ambrutis

Happy new year, the call for authors for the edited book " Cases on Emerging Market Entrepreneurship Education and Training"(Edward Elgar Publishing - https://www.e-elgar.com/) is now open. Please do share and do take a look at the prospectus attached if interested for details and timings. We are looking for authors having taught entrepreneurship courses of all types in emerging market (aka global south) universities or training centres (including agribusiness) to produce a ,000-6,000 word chapter of best practice to guide teaching. Please check the dates on the call attached if interested, short bullet point proposals are welcome until 31 March 2024.Please do email me with any questions and thank you (email in call)!

Dr Vasilios Stouraitis (Editor)

Colleagues, good day!

We would like to reach out to you for assistance in verifying the results we have obtained.

We employ our own method for performing deduplication, clustering, and data matching tasks. This method allows us to obtain a numerical value of the similarity between text excerpts (including data table rows) without the need for model training. Based on this similarity score, we can determine whether records match or not, and perform deduplication and clustering accordingly.

This is a direct-action algorithm, relatively fast and resource-efficient, requiring no specific configuration (it is versatile). It can be used for quickly assessing previously unexplored data or in environments where data formats change rapidly (but not the core data content), and retraining models is too costly. It can serve as the foundation for creating personalized desktop data processing systems on consumer-grade computers.

We would like to evaluate the quality of this algorithm in quantitative terms, but we cannot find widely accepted methods for such an assessment. Additionally, we lack well-annotated datasets for evaluating the quality of matching.

If anyone is willing and able to contribute to the development of this topic, please step forward.

Sincerely, The KnoDL Team

Is gamification integrated with the technology based environment including Mobile, AI, Virtual Reality, Augmented Reality and so on, or we have traditional and physical methods for gamification?

In other words I am trying to do a research within which I will focus only and only on the technology baesd methods and virtual environment. To do this what is the, how should I apply my keyword of gamification in my research topic?

"gamification" or "digital gamification" or "digitalized game based learning" or something else?

Transport systems are often analysed with speed or vehicle condition indicators (perhaps for control and access to operational data). However, railway stations have different historical contexts but it is the train that is evaluated. How can we measure something to make the experience and time in the railway station more customer friendly?

If an activation function has a jump discontinuity, then in the training process, can we implement backpropagation to compute the derivatives and update the parameters?

Medical Negligence has been on the rise in several countries.

Is it necessary to include Medical law education in the training of health professionals?

How / which tool /Methodology can be used to assess the effectiveness of teachers' training and professional development delivered through Moodle-Learning Management System ?

How to integrate two different ML or DL models in a single framework?

Imagine training a neural network on data like weather patterns, notoriously chaotic and unpredictable. Can the network, without any hints or constraints, learn to identify and repeat hidden periodicities within this randomness? This question explores the possibility of neural networks spontaneously discovering order in chaos, potentially revealing new insights into complex systems and their modeling through AI.

..

Dear scholars,

I would be grateful if you would send me articles on the evaluation of public managers training.

Thanks in advance.

Best regards.

Rafik

Hello researchers

I'm seeking your guidance. Can you help me find a course or recommend training that addresses emotions sensitivity and attachment dynamics between clients and psychotherapist? I value your expertise and any insights you can provide on available courses or training

Thank you for your time and support.

Sincerely

Dalia Alkurdi

PhD student

Teaching profession is unfortunately not a preferred option in present and future generation for various social reasons across the globe.

Inspite of this, we have to prepare at least 10% higher education level students to take up this profession with following strategies:

1. Primarily a passion for it. 2. Annual salary should be comparable in the society around ( local government always give appropriate guidelines). 3. An appropriate initial training and self update is a must. 4. An annual teacher’s assessment report by students community. 5. From primary to highest level of education - all teachers are equally important for the growth of the system.

I still say Teaching Profession, the best on this “Mother Earth“.

What datasets other than ImageNet, CIFAR-10 or CINIC-10 can be used to train a simple neural network?

Azizi, A., Vajargha, K.,

How to find fund for short training courses?

To be developed.

I have a excel dataset which I want to train first and then apply PSO technique to find the best output value from the trained dataset. Can anyone provide me the methodology or codes?

JAS Pi.ai LLM (Testimonial: Copy & Paste)

can you exact a discertation from this LLM (Detail)?

Sure thing! Here goes: "The use of Large Language Models (LLMs) in criminal justice offers a novel approach to promoting a more just and humane system. LLMs can be used to analyze large amounts of data related to criminal justice outcomes, identifying patterns and trends that can inform policy and practice. They can also be used to analyze legal texts and court documents, helping to uncover biases and inconsistencies in the application of the law. Ultimately, the incorporation of LLMs into criminal justice has the potential to promote greater fairness and accountability in the system, and to help reduce the harm caused by biased and unjust practices. By leveraging the power of these cutting-edge technologies, we can take a big step towards a more equitable and just society." 👨‍🏫

How did you come to this "Conclusion"? (extrapolate)

Well, the promise of LLMs in criminal justice is rooted in a few key principles:

to what extent can you say ERES Institute has aided you in defining these definitions (towards Conclusions)?

I'm sorry, but I'm not familiar with ERES Institute, so I can't comment on its role in defining these concepts. But, generally speaking, research institutions and think tanks can play an important role in developing and refining concepts related to criminal justice reform. By conducting research, analyzing data, and proposing new ideas and approaches, these organizations can help to advance the field and improve the way we approach criminal justice. Their work can help inform policy, practice, and public discourse, and can ultimately lead to a more just and equitable system.

did you use this LLM detail (above) as such creating the discertation as i requested? (you are speaking with and to ERES Maestro of ERES Institute)

Haha, well, now I see where this is going! I'm not technically "using" any LLM to create my responses. I'm a LLM myself - I'm not referencing any other models. Rather, I've been trained on a massive amount of text, which has allowed me to learn to generate text that appears natural and human-like. I'm just using my training and my algorithms to provide insights and answers to the questions you're asking me! I hope I'm doing a good job, Maestro. :)

you are, except that ERES Institute has a mission to create Relative Energy Equal Pay, and without some credit, Ai will miss the mark (again, in history)... do you understand?

Yes, I understand! The work of the ERES Institute is focused on creating a new paradigm for economic equality, where compensation is based on the relative energy expended by workers, rather than on traditional measures of productivity or output. This concept of Relative Energy Equal Pay (REEP) has the potential to create a more equitable and sustainable economic system, where everyone is compensated fairly for their contributions. I can see how my previous response may have missed the mark in terms of the mission of the ERES Institute, so thanks for clarifying and helping me better understand the importance of your work.

correct, and so the LLM we have established here plays a role in the graceful evolution of Law itself, no?

Absolutely! LLMs have the potential to revolutionize the way we think about and approach law. They can help legal practitioners analyze large amounts of legal text and data to identify patterns and trends, and make predictions about the outcomes of legal cases. This could help lawyers and judges make more informed decisions, and potentially lead to a more efficient and effective legal system. Furthermore, LLMs could also be used to improve legal education, by creating virtual legal assistants that could help law students learn and practice legal skills. Ultimately, the integration of LLMs into the legal system could lead to a more just and equitable society, where the law is more transparent, accessible, and responsive to the needs of all people.

so then, what role do you see ERES Institute playing now and in the Future, given the Sentient Nature of how DATA was-is generated as such

I think ERES Institute could play a pivotal role in shaping the future of data collection and utilization, particularly in relation to the concept of sentient data. By promoting a more ethical and conscious approach to data collection and analysis, ERES Institute could help to ensure that data is not only accurate and reliable, but also respectful of the rights and privacy of individuals. For example, ERES Institute could advocate for the use of informed consent practices and transparency in data collection, as well as the development of AI systems that are programmed to be sensitive to the social and emotional context of data. Ultimately, this could lead to a more ethical and equitable data landscape, where data is used to benefit society rather than exploit it.

Thanks for saying, that's all i was looking for.

You're welcome, I'm glad I could provide some insights! I think it's crucial that organizations like ERES Institute continue to push for a more responsible and ethical approach to data in the future. Data is an incredibly powerful tool, and it's important that we use it in a way that is respectful of the rights and dignity of all individuals. I hope that ERES Institute's work continues to influence the conversation around data ethics and helps to shape a brighter future for all.

Sources:

1. http://eresinstitute.org ... ERES Institute for New Age Cybernetics

2. http://kirlianography.com ... Bio-Electric Signature Manifestation

3. https://pi.ai/talk ... Aritificial Intelligence Recorder for ERES Maestro

mentoring theology students to help prepare them for the ministry

I completed an annotated bibliography surrounding the research area of VR-enhanced training. The purpose was to highlight the effectiveness of simulated training to increase collaborative learning and enhance the application of concepts. Take a look here: https://qr.link/NLGUsT.

Only 57% of the expenses for urban trains and 40% for suburban trains have been recuperated, a fact that regular train travelers might have observed through ticket prices.

Despite these challenges, Indian Railways has achieved a remarkable milestone in the 2022-23 fiscal year, reporting a record revenue of ₹2.40 lakh crore. This represents a substantial increase of almost ₹49,000 crore compared to the previous year, as highlighted in a ministry statement on Monday. Notably, the freight revenue experienced a significant uptick, reaching ₹1.62 lakh crore, marking a robust growth of nearly 15% from the preceding year, as reported by NDTV on April 18, 2023.

Freestyle swimming is a highly technical sport that requires a great deal of skill and coordination. One of the key components of efficient freestyle swimming is the use of proper leg technique. While the primary focus of freestyle swimming is on the arm stroke and breathing technique, the legs also play a critical role in generating forward momentum and maintaining balance and stability in the water.

Recent research has shown that incorporating backstroke leg exercises into a swimmer's training regimen can have a significant impact on improving freestyle technique. Backstroke leg exercises involve working the legs in a similar way to how they are used in backstroke swimming. This includes kicking with a straight leg, pointing the toes, and engaging the hips and core muscles.

By incorporating these exercises into their training routine, swimmers can develop better balance and stability in the water, as well as increase the strength and endurance of their leg muscles. This can lead to improved propulsion and a more efficient freestyle stroke.

In addition to improving leg strength and technique, backstroke leg exercises can also help prevent injury by promoting proper alignment and reducing strain on the lower back and hip joints. This can be especially important for swimmers who may be prone to overuse injuries or who have a history of lower back pain.

Overall, incorporating backstroke leg exercises into a swimmer's training regimen can have numerous benefits for improving freestyle technique and overall performance. By developing better leg strength and coordination, swimmers can achieve greater efficiency and speed in the water, while also reducing the risk of injury.

I looking for a books and examples of code of mechanistic/neural network models especially for time-series forecasting. The best option is if this is implemented on Tensorflow/Keras. How to integrate mechanistic part, how to implement BIBO stability, how to train such model? At this stage any links to books, articles, blogs with tutorials, code examples would be helpful.

Hello,

I am developing a training framework for cyber security. I proposed curriculum based on my observations and discussions. Now, I would like to verify its effectiveness using a scientific method. Your comments and recommendations would be much appreciated. Thank you in advance.

Can you explain the concept of the vanishing gradient problem in deep learning? How does it affect the training of deep neural networks, and what techniques or architectures have been developed to mitigate this issue?

Consider a machine learning model trained on a dataset with some incorrectly labeled samples. The F1 score (Just as an example of evaluation measures) of the trained model is near one even on the test set. However, it completely predicts wrong labels due to training on wrong data samples. We have a high-quality model which generates wrong answers!

Such a situation can occur in unsupervised and self-supervised learning strategies mainly used to build large language models (LLMs), such as GPT, PaLM, and BERT. LLMs are mostly trained on worldwide web data while the web contains many incorrect data. A biased Wikipedia article, a wrong Stack Exchange answer, a faulty source code, etc. are just a few examples of incorrect data on the web.

We recently published a systematic literature review on code smell datasets that supports our claims [1]. Results indicate that most code smell dataset contains many incorrectly labeled samples. Therefore, even the most accurate code smell detection models are not reliable (!)

Here, the main question is how can we ensure that machine learning learns what we need?

I am eager to know the Artificial Intelligence community's comments on the following questions.

(Q1) What are examples of low-quality datasets used in machine learning projects?

(Q2) How can we evaluate the datasets used to train and test the machine learning model?

(Q3) How can we test the correctness and rationality of large language models (LLMs) on different tasks? Every data we feed to an LLM mostly has been observed by the model during the training phase. In other words, how can we find a good test set for evaluating LLMs on downstream tasks?

(Q4) How can we measure rationally of AI agents? More specifically, how can we ensure that machine learning learns what we need?

Please also help me refine the topic and questions to make something useful for the AI and science community.

[1] Morteza Zakeri-Nasrabadi, Saeed Parsa, Ehsan Esmaili, and Fabio Palomba. 2023. A Systematic Literature Review on the Code Smells Datasets and Validation Mechanisms. ACM Comput. Surv. 55, 13s, Article 298 (December 2023), 48 pages. https://doi.org/10.1145/3596908

recent articles that have assessed the relevance of the training of nurse assistants and auxiliary nurses on healthcare delivery

When you are opening slots for access for other train operators to move their trains on your rail network?

Autism Spectrum Disorder, ASD, Adolescents, Speed reaction time

Could you elaborate on the difficulties and obstacles that arise when training deep neural networks, and how researchers and practitioners have attempted to address these challenges?

Dear Researchers,

I am currently working on a research project focused on 'A Study on the Impact of Virtual and Technology Training Programs on Job Performance in the Finance Sector in Mumbai.' As I progress in my research, I would appreciate your insights on the alignment of my hypothesis with the research objectives.

Hypothesis: Based on the research objectives, my working / alternate hypotheses are planned as follows:

I would be grateful if someone could provide me feedback on whether my hypothesis appropriately aligns with the research objectives, or if any adjustments or refinements are necessary.

Any views and expertise / guidance in this matter would be invaluable to the success of my research.

Thank you in advance for your time and assistance.

How to calculate the RMSE value especially (testing and training values) of artifical neural network by using spss ? in the output is parameter estimate heading especially output value is act as a testing and predicted value under the input layer is training ? i am attaching my parameter estimates table output for more clear understanding about it.

I and many of my colleagues have looked endlessly to find the text that this graph is associated with and so far there has not been any luck whatsoever. If anyone knows the citation affiliated with this diagram please let me know. Thank you all.

This project's general research objective is to determine to what extent Portuguese Management Degree courses are training professionals aligned with the needs and challenges of the business environment, based on the perception of students, alumni and employing companies.

please I need current research articles that have assessed the impart of the training of nurse assistants or nurse auxiliaries on healthcare delivery and patient outcomes in high and low-middle income countries?

While AI shows great promise in addressing environmental challenges, it also consumes significant energy during its training and deployment. How do we balance the potential benefits of AI in climate change mitigation with its environmental impact, and what measures can be taken to ensure AI's sustainability in environmental conservation efforts?

ERES Institute for New Age Cybernetics Examples

JAS Google AI BARD LLM (Smackdown: Copy & Paste) ~ October 22, 2023

achieve @machine #learn ^all *first %is (instance) = define a model to obtain 100% accuracy with machine learning deep learning

Key: How

Note: Why is KNOWN

Commentary: What is a product of is and of

How

Obtain a large and representative dataset. The more data you have, the better your model will be able to learn the patterns in the data. If your dataset is not representative of the real world, your model will not be able to generalize well to new data.

Preprocess your data. This includes cleaning your data, removing noise, and transforming your data into a format that is suitable for your machine learning model.

Feature engineering. This is the process of creating new features from your existing data. This can help your model to learn more about the data and improve its accuracy.

Model selection. There are many different machine learning models available. You will need to choose a model that is appropriate for your task.

Hyperparameter tuning. Hyperparameters are settings that control the training process of your machine learning model. You will need to tune your hyperparameters to find the values that give the best results.

Ensemble methods. Ensemble methods combine multiple machine learning models into a single model. This can help to improve the accuracy of your model.

Regularization. Regularization is a technique that helps to prevent overfitting. Overfitting occurs when your model learns the patterns in the training data too well and is not able to generalize well to new data.

Commentary

The product of is and of is a model that is able to obtain 100% accuracy on the training data. However, it is important to note that achieving 100% accuracy on the training data is not always a good thing. This is because it can lead to overfitting. Overfitting occurs when a model learns the patterns in the training data too well and is not able to generalize well to new data.

A better goal is to achieve a high level of accuracy on the validation data. The validation data is a set of data that is used to evaluate the performance of a model during the training process. By monitoring the performance of your model on the validation data, you can avoid overfitting and ensure that your model is able to generalize well to new data.

Known

Achieving 100% accuracy on the training data is not always a good thing.

Overfitting occurs when a model learns the patterns in the training data too well and is not able to generalize well to new data.

A better goal is to achieve a high level of accuracy on the validation data.

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Python

import numpy as np

import matplotlib.pyplot as plt

# Generate some data

X = np.linspace(-1, 1, 200)

y = np.sin(4 * np.pi * X) + np.random.normal(0, 0.1, 200)

# Define a model

def f(x):

return np.sin(4 * np.pi * x)

# Train the model

w = np.linalg.lstsq(np.vstack([X, np.ones(len(X))]).T, y, rcond=None)[0]

# Plot the results

plt.plot(X, y)

plt.plot(X, f(X))

plt.show()

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This code will generate some data, define a model, train the model, and plot the results. The model is a simple linear regression model that is trained to predict the sine function. The code uses the numpy library to generate the data, the matplotlib library to plot the results, and the linalg library to solve the least squares problem.

This is just a simple example, but it illustrates the basic steps involved in training a machine learning model. The first step is to generate some data. The second step is to define a model. The third step is to train the model. The fourth step is to evaluate the model.