This is currently in an Early Bird Beta access, meaning we are still going to be continually adding content to the course (even though we are already at over 22 hours of content!) Since we're still adding content and taking student feedback as we complete the course through the start of 2021, students who enroll now will get access to a wide variety of benefits! NOTE: The additional content will focus on Machine Learning. We'll be going in-depth on all the major machine learning algorithms including both theory and practical examples with code. Welcome to the Learn Data Science and Machine Learning with R from A-Z Course! In this practical, hands-on course you'll learn how to program in R and how to use R for effective data analysis, visualization and how to make use of that data in a practical manner.

Analyzing data and building machine learning models is one thing. Packaging these analyses and models such that they are sharable is a different ball game altogether. This course aims at teaching you the fastest and easiest way to build and share data applications using Streamlit. You don't need any experience in building front-end applications for this.

Through the EpiMed Open Course initiative, the Institut pour l’Avancée des Biosciences (IAB) and Grenoble Alpes University have launched courses available on Youtube. Researcher Ekaterina Flin offers here an introduction to artificial intelligence for the analysis of biological data and the study of cancer. The course provides an overview of application areas and scientific questions […]

Humans, as the most powerful learners on the planet, have accumulated a lot of learning skills, such as learning through tests, interleaving learning, self-explanation, active recalling, to name a few. These learning skills and methodologies enable humans to learn new topics more effectively and efficiently. We are interested in investigating whether humans' learning skills can be borrowed to help machines to learn better. Specifically, we aim to formalize these skills and leverage them to train better machine learning (ML) models. To achieve this goal, we develop a general framework -- Skillearn, which provides a principled way to represent humans' learning skills mathematically and use the formally-represented skills to improve the training of ML models. In two case studies, we apply Skillearn to formalize two learning skills of humans: learning by passing tests and interleaving learning, and use the formalized skills to improve neural architecture search. Experiments on various datasets show that trained using the skills formalized by Skillearn, ML models achieve significantly better performance.

Advanced Neural Networks in R - A Practical Approach Boost your data science skills - learn to build and train complex neural network using the R program. Neural networks are powerful predictive tools that can be used for almost any machine learning problem with very good results. If you want to break into deep learning and artificial intelligence, learning neural networks is the first crucial step. This course contains four comprehensive sections. Learn to use multilayer perceptrons to make predictions for both categorical and continuous variables.

Welcome to KGP Talkie's Natural Language Processing course. It is designed to give you a complete understanding of Text Processing and Mining with the use of State-of-the-Art NLP algorithms in Python. We will learn Spacy in details and we will also explore the uses of NLP in real-life. This course covers the basics of NLP to advance topics like word2vec, GloVe, Deep Learning for NLP like CNN, ANN, and LSTM. I will also show you how you can optimize your ML code by using various tools of sklean in python.

In this Scikit-learn tutorial introduces you to machine learning in Python and introduction to Machine Learning with Scikit-Learn. It will explain how to use scikit-learn to do machine learning. Welcome to this video course on Scikit-Learn. This course will explain how to use scikit-learn to do machine learning. Methods to load Toy Datasets and exploring their feature names, number of instances and other details have been shown.

Welcome to PyTorch: Deep Learning and Artificial Intelligence! Although Google's Deep Learning library Tensorflow has gained massive popularity over the past few years, PyTorch has been the library of choice for professionals and researchers around the globe for deep learning and artificial intelligence. Is it possible that Tensorflow is popular only because Google is popular and used effective marketing? Why did Tensorflow change so significantly between version 1 and version 2? Was there something deeply flawed with it, and are there still potential problems? It is less well-known that PyTorch is backed by another Internet giant, Facebook (specifically, the Facebook AI Research Lab - FAIR).

BEGIN ARTICLE PREVIEW: Test, Measurement & Analytics WHITEPAPERS How a powertrain manufacturer optimized its welding process using advanced image algorithms from a platform that extracts key features from images, analyzes them, and informs MES decisions in near real-time. How auto-manufacturers can apply ML & AI algorithms to enhance image analytics on their factory floor and to ensure higher product quality? Discover the next generation visual inspection in our new case study. In this case study , you will learn about: Current limitations of image inspection in the manufacturing industry. The O+ end-to-end solution, which brings machine learning and deep learning to image analysis in the production line. How a powertrain manufacturer deployed OptimalPlus’ software on the edge and utilized its image analysis capabilities to optimize the welding process. Despite its great potentia

Experts say that artificial intelligence (AI) is likely to have a bigger impact on health care than anything the field has experienced in our lifetime. During the COVID-19 pandemic, we're seeing how AI is helping clinicians screen for, and diagnose, COVID-19; it's aiding researchers' efforts to develop new drugs and vaccines. Though some health care workers worry that AI tools could replace their jobs, in fact AI is driving innovation, process improvements and better patient outcomes. It's enhancing providers' ability to care for more patients safely. The American Hospital Association and Microsoft now offer a free, one-hour course, for continuing education credits, to guide health care teams through key considerations and specific actions for AI's responsible and strategic implementation.