Free Download Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition [PDF] Full EbookThe Real Books
A book on Machine Learning in Trading that helps you learn and gain an edge in the trading domain with Machine Learning and related concepts. It presents the core set and principles of Machine Learning in an easy to understand language, all in a compact
For a list of free machine learning books available for download, go here. For a list of professional machine learning events, go here. For a list of (mostly) free machine learning courses available online, go here. For a list of blogs and newsletters on data science and machine learning,...
A curated list of awesome responsible machine learning resources. - jphall663/awesome-machine-learning-interpretability
grt - The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, C++ machine learning library designed for real-time gesture recognition.Reinforcement LearningRLtools - The fastest deep reinforcement learning library for continuous control, implemented header-only in pure, dependency-free ...
The two demo data files are available in the download that accompanies this article. Understanding the Data Most machine learning problems start with analysis and preparation of the available data, and that’s the case when using ML.NET CLI and AutoML. The training data has 1,000 items and ...
This article assumes you have familiarity working with command-line programs and a rough idea of what neural networks are, but doesn’t assume you’re a machine learning (ML) expert or know anything about CNTK. You can also get the code and data from the accompanying download. ...
Core ML delivers blazingly fast performance on Apple devices with easy integration of machine learning and AI models into your apps. Convert models from popular training libraries using Core ML Tools or download ready-to-use Core ML models. Easily preview models and understand their performance right...
The nitty-gritty of deep learning involves lots of parallel multiplication and sums over very large arrays of floating-point numbers. GPU support noticeably speeds up even trivial ML projects, and low-level performance is an area where the various large projects compete with each ot...
As with every machine learning implementation, the first step is to load in the training data. However in this example we are taking it 1 step further into machine learning. In the KNN examples we had the download and upload speed as features. We did not refer to them as features, as ...