Information Technology: Instructional Materials

Lecture 1/16 : Introduction


Neural Networks for Machine Learning by Geoffrey Hinton [Coursera 2013] 1A Why do we need machine learning?

Andrew Ng launches 'AI for Everyone,' a new Coursera program aimed at business professionals


Andrew Ng, a computer scientist who led Google's AI division, Google Brain, and formerly served as vice president and chief scientist at Baidu, is a veritable celebrity in the artificial intelligence (AI) industry. After leaving Baidu, he debuted an online curriculum of classes centered around machine learning -- Ng was the keynote speaker at the AI Frontiers Conference in November 2017, and this year unveiled the AI Fund, a $175 million incubator that backs small teams of experts looking to solve key problems using machine learning. Oh, and he's also chairman of AI cognitive behavioral therapy startup Woebot; sits on the board of driverless car company; Yet somehow, he found time to put together a new online training course -- "AI for Everyone" -- that seeks to demystify AI for business executives.

Top 10 Machine Learning, Deep Learning, and Data Science Courses for Beginners (Python and R) - DZone AI


The first programming exercise "Twitter Sentiment Analysis in Python" is both fun and challenging, where you analyze tons of twitter message to find out the sentiments e.g.

How to Speed Up Deep Learning Inference Using TensorRT NVIDIA Developer Blog


Welcome to this introduction to TensorRT, our platform for deep learning inference. You will learn how to deploy a deep learning application onto a GPU, increasing throughput and reducing latency during inference. TensorRT provides APIs and parsers to import trained models from all major deep learning frameworks. It then generates optimized runtime engines deployable in the datacenter as well as in automotive and embedded environments. Applications deployed on GPUs with TensorRT perform up to 40x faster than CPU-only platforms. This tutorial uses a C example to walk you through importing an ONNX model into TensorRT, applying optimizations, and generating a high-performance runtime engine for the datacenter environment.

Chapter 1: Bird's Eye View of Applied Machine Learning - Data Science Primer


Welcome to our 7-part mini-course on data science and applied machine learning! Over these 7 chapters, our goal is to provide you with an end-to-end blueprint for applied machine learning, while keeping this as actionable and succinct as possible. With that, let's get started with a bird's eye view of the machine learning workflow. One really cool (optional) challenge you can do in the next hour is training your first machine learning model! That's right, we've put together a complete step-by-step tutorial for training a model that can predict wine quality.

Best deals for Nov 7: Save on Apple MacBook Air, AirPods, Instant Pot, iPad Mini 4, Microsoft Surface Book 2, and more


We hope you have your holiday shopping game face on because the details today are pretty excellent. We're rounding up the best deals from Amazon, Walmart, Best Buy, and Macy's on Apple products, laptops and accessories, kitchen appliances, and even Amazon's own devices. We're also highlighting deals on Udemy online classes in case you feel inspired to learn a little something. There are a number of Apple products on sale, such as the Apple MacBook (mid-2017) 12-inch laptop, which is priced at $999.99, or $400 off its list price. It seems that the previous generation is on sale now before the new MacBook Air 2018 model hits store shelves .

A Gentle Introduction to LSTM Autoencoders


An LSTM Autoencoder is an implementation of an autoencoder for sequence data using an Encoder-Decoder LSTM architecture. Once fit, the encoder part of the model can be used to encode or compress sequence data that in turn may be used in data visualizations or as a feature vector input to a supervised learning model. In this post, you will discover the LSTM Autoencoder model and how to implement it in Python using Keras. A Gentle Introduction to LSTM Autoencoders Photo by Ken Lund, some rights reserved. An autoencoder is a neural network model that seeks to learn a compressed representation of an input.

List Of Free Online Courses On Artificial Intelligence MarkTechPost


Note: If you find some more AI courses which are free then please feel free to send us via email. We will add your name here in the list at the bottom as a volunteer.