# Tag: PyTorch (17)

**Top Stories, May 14-20: Data Science vs Machine Learning vs Data Analytics vs Business Analytics; Implement a YOLO Object Detector from Scratch in PyTorch**- May 21, 2018.

Also: An Introduction to Deep Learning for Tabular Data; 9 Must-have skills you need to become a Data Scientist, updated; GANs in TensorFlow from the Command Line: Creating Your First GitHub Project; Complete Guide to Build ConvNet HTTP-Based Application**How to Implement a YOLO (v3) Object Detector from Scratch in PyTorch: Part 1**- May 17, 2018.

The best way to go about learning object detection is to implement the algorithms by yourself, from scratch. This is exactly what we'll do in this tutorial.**KDnuggets™ News 18:n20, May 16: PyTorch Tensor Basics; Data Science in Finance; Executive Guide to Data Science**- May 16, 2018.

PyTorch Tensor Basics; Top 7 Data Science Use Cases in Finance; The Executive Guide to Data Science and Machine Learning; Data Augmentation: How to use Deep Learning when you have Limited Data**Simple Derivatives with PyTorch**- May 14, 2018.

PyTorch includes an automatic differentiation package, autograd, which does the heavy lifting for finding derivatives. This post explores simple derivatives using autograd, outside of neural networks.**PyTorch Tensor Basics**- May 11, 2018.

This is an introduction to PyTorch's Tensor class, which is reasonably analogous to Numpy's ndarray, and which forms the basis for building neural networks in PyTorch.**Ultra-compact workstation for top deep learning frameworks**- Apr 27, 2018.

For workstation development platforms purpose-built for Tensorflow, PyTorch, Caffe2, MXNet, and other DL frameworks, the solution is BOXX. We're bringing deep learning to your deskside with the all-new APEXX W3!**KDnuggets™ News 18:n16, Apr 18: Key Algorithms and Statistical Models; Don’t learn Machine Learning in 24 hours; Data Scientist among the best US Jobs in 2018**- Apr 18, 2018.

Also: Top 10 Technology Trends of 2018; 12 Useful Things to Know About Machine Learning; Robust Word2Vec Models with Gensim & Applying Word2Vec Features for Machine Learning Tasks; Understanding What is Behind Sentiment Analysis - Part 1; Getting Started with PyTorch**Getting Started with PyTorch Part 1: Understanding How Automatic Differentiation Works**- Apr 11, 2018.

PyTorch has emerged as a major contender in the race to be the king of deep learning frameworks. What makes it really luring is it’s dynamic computation graph paradigm.**Comparing Deep Learning Frameworks: A Rosetta Stone Approach**- Mar 26, 2018.

A Rosetta Stone of deep-learning frameworks has been created to allow data-scientists to easily leverage their expertise from one framework to another.**Deep Learning Development with Google Colab, TensorFlow, Keras & PyTorch**- Feb 20, 2018.

Now you can develop deep learning applications with Google Colaboratory - on the free Tesla K80 GPU - using Keras, Tensorflow and PyTorch.**A Simple Starter Guide to Build a Neural Network**- Feb 5, 2018.

This guide serves as a basic hands-on work to lead you through building a neural network from scratch. Most of the mathematical concepts and scientific decisions are left out.**Top 10 Videos on Deep Learning in Python**- Nov 17, 2017.

Playlists, individual tutorials (not part of a playlist) and online courses on Deep Learning (DL) in Python using the Keras, Theano, TensorFlow and PyTorch libraries. Assumes no prior knowledge. These videos cover all skill levels and time constraints!**Ranking Popular Deep Learning Libraries for Data Science**- Oct 23, 2017.

We rank 23 open-source deep learning libraries that are useful for Data Science. The ranking is based on equally weighing its three components: Github and Stack Overflow activity, as well as Google search results.**Top KDnuggets tweets, Oct 04-10: Using #MachineLearning to Predict, Explain Attrition; Tidyverse, an opinionated #DataScience Toolbox in R**- Oct 11, 2017.

Also #MachineLearning: Understanding Decision Tree Learning; #PyTorch tutorial distilled - Moving from #TensorFlow to PyTorch.**PyTorch or TensorFlow?**- Aug 29, 2017.

PyTorch is better for rapid prototyping in research, for hobbyists and for small scale projects. TensorFlow is better for large-scale deployments, especially when cross-platform and embedded deployment is a consideration.**Top KDnuggets tweets, Aug 2-8: PyTorch: concise overview of the framework and its tensor implementation**- Aug 9, 2017.

Also: What is the most important step in a #MachineLearning project? #MachineLearning Algorithms: a concise technical overview; McKinsey state of #MachineLearning and #AI.**Design by Evolution: How to evolve your neural network with AutoML**- Jul 20, 2017.

The gist ( tl;dr): Time to evolve! I’m gonna give a basic example (in PyTorch) of using evolutionary algorithms to tune the hyper-parameters of a DNN.