Ethical Artificial Intelligence
Discrimination and fairness in AI and machine learning: How to detect and mitigate bias in the financial services industry
Discrimination and fairness in AI and machine learning: - A topic and debate.. Nicely written
GC Antiviral / Viricidal Graphene Inks
Although existing personal protective equipment (PPE) can filter out 95% of harmful bacteria and viruses, few can actually kill coronaviruses in particular. Research has shown that combining graphene oxide (GO) with known antivirals significantly enhances their virus-killing performance.
Although existing personal protective equipment (PPE) can filter out 95% of harmful bacteria and viruses - Is there any improvement in the system?
Natural Language Processing (NLP) Simplified : A Step-by-step Guide
As researchers push the boundaries of Natural Language Processing (NLP), the technology is becoming more embedded in our everyday lives. These advances will result in significant changes to the way we live. As an important facet of artificial intelligence, natural language processing is going to contribute to the proverbial invasion of robots in the workplace, so if companies are going to remain competitive, they must start to prepare. This document will throw some light on the basics of NLP.
Named Entity Recognition. Sentiment Analysis. Text Summarization. Aspect Mining. Topic Modeling. These are the Natural Language Processing (NLP), techniques.
What are some of the latest techniques in data science
What are some of the latest techniques in data science and machine learning. Can we bring down some of the trending one and its use?
Thanks for your comment. Lets keep adding more and more algorithms and techniques in it...
Dynamometer-Card Data Classification Uses Machine Learning
This is another successful use case of the in the application of machine learning in the petroleum industry.A dynamometer-card is a data acquisition system in the rod pumping system in a petroleum production field. Analyzing this data delivers valuable insight into the status of the pump and can indicate if future action is required. I have shared a report on my LinkedIn page explaining how machine learning is used to improve the surveillance of beam pumps using the dynamometer-card data and machine-learning techniques,Interested readers can access my page: https://www.linkedin.com/posts/fataianifowose_dynamometer-card-classification-uses-machine-activity-6644544993019129856-PdYB
This article was really interesting.,How machine learning is used to improve the surveillance of beam pumps using the dynamometer-card data and machine-learning techniques,Thank you.
Tools for Data science
What are the famous tools aperson should be aware of while working in Data science ?
Julia, R, Python, etc.RStudio, PyCharm, Notepad++, These are the.some tools working in Data science
Communication is key to sharing your contributions to AI
Hi everyone,Knowing that communication is key to showcasing our contributions to the AI and ML community, I shared through my LinkedIn page some quick tips for running successful meetings whether virtually or physically. I hope it will be of benefit to someone here.https://www.linkedin.com/posts/fataianifowose_wfh-during-corona-six-quick-tips-for-running-activity-6651854346617176064-XlG1
tips for running successful meetings whether virtually or physically - thanks for sharing this across
Difference between correlation and causation
Correlation is a statistic that measures the strength and direction of the associations between two or more variables. Causation, on the other hand, is a relationship that describes cause and effect. “Correlation does not imply causation” is a famous quote that warns us about the dangers of the very common practice of looking at a strong correlation and assuming causality.
Correlation is a statistic that measures the strength and direction of the associations between two or more variables. - Agree
Regarding with Gradient Descent in Data Science
Hello Everyone, I am learning Data Science and My few interviews are scheduled next to next week on skype. Can anyone explain in-depth information about gradient descent in Data Science, As my research, the degree of change in the output of a function relating to the changes made to the inputs is known as a gradient. It measures the change in all weights with respect to the change in error. A gradient can also be comprehended as the slope of a function, this is according to this post https://hackr.io/blog/data-science-interview-questions when I was searching for this query. Can anyone know this is the perfect description of Gradient Descent?
Can anyone explain in-depth information about gradient descent in Data Science, As my research, - Any specific?
What are the best skills required for NLP experts
Ideally candidates for job roles in Natural Language Processing (NLP) should have command over both linguistics and computers. He should understand the concepts of linguistics like speech recognition, information extraction, sentence fragmentation, parts of speech, and so on. Python programming language is one of the best suited for NLP, many tools and libraries are available for supporting NLP tasks.NLTK, the most widely-mentioned NLP library available for Python.
1. Computer Science Fundamentals and Programming2. Probability and Statistics3. Data Modeling and Evaluation4. Applying Machine Learning Algorithms and Libraries5. Software Engineering and System Design