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Introduction to AI & ML techniques in Drug Discovery

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A perfect course for Bachelors / Masters / PhD students who are getting started into Drug Discovery research. This course is specially designed keeping in view of beginner level knowledge on Artificial Intelligence, Machine learning and computational drug discovery applications for science students. By the end of this course participants will be equipped with the basic knowledge required to navigate their drug discovery project making use of the Artificial Intelligence and Machine learning based tools.Who this course is for:


Moving from data science to machine learning engineering

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For the last 20 years, machine learning has been about one question: Can we train a model to do something? Something, of course, can be any task. Predict the next word in a sentence, recognize faces in a photo, generate a certain sound. The goal was to see if machine learning worked, if we could make accurate predictions. What can we build with these models, and how can we do it?


Global Big Data Conference

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Amid a growing backlash over AI's racial and gender biases, numerous tech giants are launching their own ethics initiatives -- of dubious intent. The schemes are billed as altruistic efforts to make tech serve humanity. But critics argue their main concern is evading regulation and scrutiny through "ethics washing." At least we can rely on universities to teach the next generation of computer scientists to make. Only 15% of instructors and professors said they're teaching AI ethics, and just 18% of students indicated they're learning about the subject.



Study: Only 18% of data science students are learning about AI ethics

#artificialintelligence

Amid a growing backlash over AI's racial and gender biases, numerous tech giants are launching their own ethics initiatives -- of dubious intent. The schemes are billed as altruistic efforts to make tech serve humanity. But critics argue their main concern is evading regulation and scrutiny through "ethics washing." At least we can rely on universities to teach the next generation of computer scientists to make. Only 15% of instructors and professors said they're teaching AI ethics, and just 18% of students indicated they're learning about the subject.


2 books to strengthen your command of python machine learning

#artificialintelligence

This post is part of "AI education", a series of posts that review and explore educational content on data science and machine learning. Mastering machine learning is not easy, even if you're a crack programmer. I've seen many people come from a solid background of writing software in different domains (gaming, web, multimedia, etc.) thinking that adding machine learning to their roster of skills is another walk in the park. And every single one of them has been dismayed. I see two reasons for why the challenges of machine learning are misunderstood. First, as the name suggests, machine learning is software that learns by itself as opposed to being instructed on every single rule by a developer.



Linear Programming for Data Science and Business Analysis

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In this course you will learn all about the mathematical optimization of linear programming for data science and business analytics. This course is very unique and have its own importance in their respective disciplines. The data science and business study heavily rely on optimization. Optimization is the study of analysis and interpreting mathematical data under the special rules and formula. The length of the course is more than 6 hours and there are total more than 4 sections in this course.


Maths for Data Science and Machine Learning

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This course is bundle of two courses of linear algebra and probability and statistics. So, students will learn complete contents of probability and statistics and linear algebra. It is not like that you will not complete all the contents in this 7 hours videos course. This is a beautiful course and I have designed this course according to the need of the students. WHERE THIS COURSE IS APPLICABLE?


Social Distance Detector with Python, YOLOv4, Darknet, and OpenCV

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As the spread of COVID 19 continues, communities are told to reduce close contact between individuals. This is called Social Distancing, as it is a necessary and effective way to slow down the spread of the virus. As a data science student, I came with a solution to identify whether people actually follow the social distancing protocol of staying at least 6 feet from each other. YOLO stands for You Only Look Once. It's a fast operating object detection system that can recognize various object types in a single frame more precisely than other detection systems.