# Tag: TensorFlow

**Getting Started with Deep Learning**- Mar 24, 2017.

This post approaches getting started with deep learning from a framework perspective. Gain a quick overview and comparison of available tools for implementing neural networks to help choose what's right for you.**Top /r/MachineLearning Posts, February: Oxford Deep NLP Course; Data Visualization for Scikit-learn Results**- Mar 6, 2017.

Oxford Deep NLP Course; scikit-plot: Data Visualization for Scikit-learn Results; Machine Learning at Berkeley's ML Crash Course: Neural Networks; Predicting parking difficulty with machine learning; TensorFlow 1.0 Release**An Overview of Python Deep Learning Frameworks**- Feb 27, 2017.

Read this concise overview of leading Python deep learning frameworks, including Theano, Lasagne, Blocks, TensorFlow, Keras, MXNet, and PyTorch.**The Gentlest Introduction to Tensorflow – Part 4**- Feb 22, 2017.

This post is the fourth entry in a series dedicated to introducing newcomers to TensorFlow in the gentlest possible manner, and focuses on logistic regression for classifying the digits of 0-9.**The Gentlest Introduction to Tensorflow – Part 3**- Feb 21, 2017.

This post is the third entry in a series dedicated to introducing newcomers to TensorFlow in the gentlest possible manner. This entry progresses to multi-feature linear regression.**Top /r/MachineLearning Posts, January: TensorFlow Updates; AlphaGo in the Wild; Self-Driving Mario Kart**- Feb 7, 2017.

TensorFlow 1.0.0-alpha; Unknown bot repeatedly beats top Go players online - so far it's undefeated; TensorKart: self-driving MarioKart with TensorFlow; GTA V integration into Universe is now open-source; Keras will be added to core TensorFlow at Google**Top KDnuggets tweets, Jan 25-31: Python implementations of Andrew Ng #MachineLearning MOOC exercises**- Feb 1, 2017.

#Python implementations of Andrew Ng #MachineLearning MOOC exercises; This repository contains the entire #Python #DataScience Handbook; What are the best #visualizations of #MachineLearning algorithms? Learn #TensorFlow and #DeepLearning, without a PhD.**Top /r/MachineLearning Posts, 2016: Google Brain AMA; Google Machine Learning Recipes; StarCraft II AI Research Environment**- Jan 11, 2017.

Google Brain AMA; Google Machine Learning Recipes; StarCraft II AI Research Environment; Huggable Image Classifier; xkcd: Linear Regression; AlphaGO WINS!; TensorFlow Fizzbuzz**Top KDnuggets tweets, Dec 14-20: False positives versus false negatives: Best explanation ever**- Dec 21, 2016.

Also #MachineLearning, #AI experts: Main Developments 2016, Key Trends 2017; Official code repository for #MachineLearning with #TensorFlow book; Top 10 Essential Books for the #Data Enthusiast.**What we can learn from AI mistakes**- Dec 19, 2016.

Because of recent innovations and research in AI, we have seen AI performing best in some very important tasks and even worst in even simple tasks. So the question is, Why is it that AI can look so brilliant and so stupid at the same time?**Predictions for Deep Learning in 2017**- Dec 19, 2016.

The first hugely successful consumer application of deep learning will come to market, a dominant open-source deep-learning tool and library will take the developer community by storm, and more Deep Learning predictions.**New Book: TensorFlow for Machine Intelligence – KDnuggets Holiday Offer**- Dec 12, 2016.

TensorFlow for Machine Intelligence is a hands-on introduction to learning algorithms and the "TensorFlow book for humans." For a limited holiday special, KDnuggets readers get a 40% discount, available here.**Implementing a CNN for Human Activity Recognition in Tensorflow**- Nov 21, 2016.

In this post, we will see how to employ Convolutional Neural Network (CNN) for HAR, that will learn complex features automatically from the raw accelerometer signal to differentiate between different activities of daily life.**Introduction to Trainspotting: Computer Vision, Caltrain, and Predictive Analytics**- Nov 1, 2016.

We previously analyzed delays using Caltrain’s real-time API to improve arrival predictions, and we have modeled the sounds of passing trains to tell them apart. In this post we’ll start looking at the nuts and bolts of making our Caltrain work possible.**MLDB: The Machine Learning Database**- Oct 17, 2016.

MLDB is an opensource database designed for machine learning. Send it commands over a RESTful API to store data, explore it using SQL, then train machine learning models and expose them as APIs.**Urban Sound Classification with Neural Networks in Tensorflow**- Sep 12, 2016.

This post discuss techniques of feature extraction from sound in Python using open source library Librosa and implements a Neural Network in Tensorflow to categories urban sounds, including car horns, children playing, dogs bark, and more.**Top /r/MachineLearning Posts, August: Google Brain AMA, Image Completion with TensorFlow, Japanese Cucumber Farming**- Sep 5, 2016.

Google Brain AMA; Image Completion with Deep Learning in TensorFlow; Japanese Cucumber Farming; Andrew Ng's machine learning class in Python; Google Brain datasets for robotics research**New Book: TensorFlow for Machine Intelligence, KDnuggets Offer**- Aug 30, 2016.

TensorFlow for Machine Intelligence is a hands-on introduction to learning algorithms and the "TensorFlow book for humans." KDnuggets readers get a 25% discount, available here.**Top KDnuggets tweets, Aug 17-23: Approaching (Almost) Any #MachineLearning Problem; #Database Nirvana – can one query language rule them all?**- Aug 24, 2016.

In Search of #Database Nirvana - can one query language rule them all? Google Cloud Datalab: #Jupyter meets #TensorFlow, #cloud meets local deployment; Approaching (Almost) Any #MachineLearning Problem; The Gentlest Introduction to Tensorflow Part 1.**KDnuggets™ News 16:n31, Aug 24: 10 Algo Machine Learning Engineers Need to Know; How to Become a Data Scientist; Gentle Tensorflow**- Aug 24, 2016.

The 10 Algorithms Machine Learning Engineers Need to Know; How to Become a Data Scientist - Part 1; The Gentlest Introduction to Tensorflow - Part 1; Approaching (Almost) Any Machine Learning Problem.**The Gentlest Introduction to Tensorflow – Part 2**- Aug 19, 2016.

Check out the second and final part of this introductory tutorial to TensorFlow.**The Gentlest Introduction to Tensorflow – Part 1**- Aug 17, 2016.

In this series of articles, we present the gentlest introduction to Tensorflow that starts off by showing how to do linear regression for a single feature problem, and expand from there.**Top KDnuggets tweets, Jul 27 – Aug 2: Understanding neural networks with Google TensorFlow Playground; Getting Started with Data Science in Python**- Aug 3, 2016.

Understanding neural networks with Google TensorFlow Playground; The 100 Best-Funded #Analytics #DataScience #Startups; Great tutorial: Getting Started with #DataScience - #Python; #MachineLearning over 1M hotel reviews: interesting insights.**Deep Learning For Chatbots, Part 2 – Implementing A Retrieval-Based Model In TensorFlow**- Jul 29, 2016.

Check out part 2 of this tutorial on building chatbots with deep neural networks. This part gets practical, and using Python and TensorFlow to implement.**Top KDnuggets tweets, Jul 20-26: Math-free simple explanation: #DeepLearning Demystified; Are #Humans Becoming More Machine-Like?**- Jul 27, 2016.

Finally, a #TensorFlow book for humans; Great math-free simple intro explanation video: Deep Learning Demystified; Does #sentiment analysis work? A tidy analysis of Yelp reviews; JupyterLab: the next generation of the #Jupyter Notebook**Multi-Task Learning in Tensorflow: Part 1**- Jul 20, 2016.

A discussion and step-by-step tutorial on how to use Tensorflow graphs for multi-task learning.**Recursive (not Recurrent!) Neural Networks in TensorFlow**- Jun 30, 2016.

Learn how to implement*recursive*neural networks in TensorFlow, which can be used to learn tree-like structures, or directed acyclic graphs.**Top /r/MachineLearning Posts, May: TensorFlow Tricks; Machine Learning Tutorials; Google TPUs**- Jun 1, 2016.

May on /r/MachineLearning was all about tutorials, TensorFlow, Google hardware, Deep Learning machine installations, and some laughs.**Introduction to Recurrent Networks in TensorFlow**- May 31, 2016.

A straightforward, introductory overview of implementing Recurrent Neural Networks in TensorFlow.**The Good, Bad & Ugly of TensorFlow**- May 24, 2016.

A survey of six months of rapid evolution (+ tips/hacks and code to fix the ugly stuff) using TensorFlow. Get some great advice from the trenches.**Top KDnuggets tweets, May 11-17: Vote: What software you used for Analytics, Data Mining, Data Science projects?**- May 18, 2016.

Vote: What software you used for Analytics, Data Mining, Data Science projects? Useful #Cheatsheet: #Python, R #rstats code for #MachineLearning Algorithms; TPOT: A #Python Tool for Automating Data Science; Randomize Acceptance of Borderline Research Papers, save 25 reviewer person-years.**How to Quantize Neural Networks with TensorFlow**- May 4, 2016.

The simplest motivation for quantization is to shrink neural network representation by storing the min and max for each layer. Learn more how to perform quantization for deep neural networks.**Top KDnuggets tweets, Apr 27 – May 3: Trifecta: Python, Machine Learning, and Dueling Languages; Fun game 4 #MachineLearning newbies**- May 4, 2016.

Trifecta: #Python, #MachineLearning, + Dueling Languages; Cartoon: When #Automation Goes Too Far; #AI Speed: 2-year old #xkcd cartoon: cannot check if a photo has a bird; Removing Duplicates in #BigData.**Top /r/MachineLearning Posts, April: New Google Machine Learning Videos, Deep Learning Book, TensorFlow Playground**- May 2, 2016.

Check out the most popular topics on Reddit's Machine Learning subreddit from April, including TensorFlow, deep learning, tutorials, self-reflection, and free books.**Top 10 IPython Notebook Tutorials for Data Science and Machine Learning**- Apr 22, 2016.

A list of 10 useful Github repositories made up of IPython (Jupyter) notebooks, focused on teaching data science and machine learning. Python is the clear target here, but general principles are transferable.**Tricking Deep Learning**- Apr 8, 2016.

Deep neural networks have had remarkable success with many tasks including image recognition. Read this overview regarding deep learning trickery, and why you should be cognizant.**Top /r/MachineLearning Posts, February: AlphaGo, Distributed TensorFlow, Neural Network Image Enhancement**- Mar 2, 2016.

In February on /r/MachineLearning, we get a run-down of the AlphaGo matches, Distributed TensorFlow is released, convolutional neural nets are cleaning Star Wars images, vintage science is on parade, military machine learning is criticized, and the overwhelmed researcher is given advice.**KDnuggets™ News 16:n08, Mar 2: Citizen Data Scientist Mirage; Spark Tipping Point; 80% Machine Learning**- Mar 2, 2016.

The Mirage of a Citizen Data Scientist; Why Spark Reached the Tipping Point in 2015; The Machine Learning Problem of The Next Decade; How The Algorithm Economy And Containers Are Changing The Apps.**Distributed TensorFlow Has Arrived**- Mar 1, 2016.

Google has open sourced its distributed version of TensorFlow. Get the info on it here, and catch up on some other TensorFlow news at the same time.**Opening Up Deep Learning For Everyone**- Feb 19, 2016.

Opening deep learning up to everyone is a noble goal. But is it achievable? Should non-programmers and even non-technical people be able to implement deep neural models?**Scikit Flow: Easy Deep Learning with TensorFlow and Scikit-learn**- Feb 12, 2016.

Scikit Learn is a new easy-to-use interface for TensorFlow from Google based on the Scikit-learn fit/predict model. Does it succeed in making deep learning more accessible?**KDnuggets™ News 16:n04, Feb 3: Is Deep Learning Overhyped? Businesses Will Need 1M Data Scientists**- Feb 3, 2016.

New Poll: Deep Learning - does reality match the hype?; Is Deep Learning Overhyped?; Businesses Will Need One Million Data Scientists by 2018; KDnuggets New Responsive, Mobile-Friendly Design.**Deep Learning with Spark and TensorFlow**- Jan 28, 2016.

The integration of TensorFlow with Spark leverages the distributed framework for hyperparameter tuning and model deployment at scale. Both time savings and improved error rates are demonstrated.**Google Launches Deep Learning with TensorFlow MOOC**- Jan 26, 2016.

Google and Udacity have partnered for a new self-paced course on deep learning and TensorFlow, starting immediately.**KDnuggets™ News 16:n01, Jan 13: Detect Fake Data Scientists; Tensorflow is Terrific; More arXiv Deep Learning, explained**- Jan 12, 2016.

20 Questions to Detect Fake Data Scientists; TensorFlow is Terrific; 5 More arXiv Deep Learning Papers, Explained; What questions can data science answer?**7 Steps to Understanding Deep Learning**- Jan 11, 2016.

There are many deep learning resources freely available online, but it can be confusing knowing where to begin. Go from vague understanding of deep neural networks to knowledgeable practitioner in 7 steps!**Top 5 Deep Learning Resources, January**- Jan 7, 2016.

There is an increasing volume of deep learning research, articles, blog posts, and news constantly emerging. Our Deep Learning Reading List aims to make this information easier to digest.**Top KDnuggets tweets, Dec 28 – Jan 03: TensorFlow is Terrific; Data Science in Python 100 Interview Questions**- Jan 4, 2016.

TensorFlow is Terrific - A Sober Take on Google Deep Learning; Data Science in Python 100 Interview Questions and Answers; 20 Questions to Detect Fake Data Scientists; There are only 5 questions #MachineLearning can answer.**Top /r/MachineLearning Posts, December: The Secret Sauce, OpenAI, Google vs. Facebook**- Jan 4, 2016.

December on /r/MachineLearning: Is TensorFlow Google's "secret sauce?", AI leaders unite, an extensive curated list of machine learning resources grows, Google vs. Facebook, and Deep Q Pong.**TensorFlow is Terrific – A Sober Take on Deep Learning Acceleration**- Dec 30, 2015.

TensorFlow does not change the world. But it appears to be the best, most convenient deep learning library out there.**KDnuggets™ News 15:n42, Dec 29: Where did you apply Analytics? 5 ways Data Scientists keep learning**- Dec 29, 2015.

Poll: Industries/Fields where you applied Analytics, Data Mining, Data Science in 2015; 5 Ways Data Scientists Keep Learning After College; Lessons from 2M Machine Learning Models on Kaggle; 10 BI Trends for 2016.**Top KDnuggets tweets, Dec 14-20: DeepLearning in a Nutshell: History and Training; Top 10 #MachineLearning Algorithms, updated**- Dec 21, 2015.

Top 10 #MachineLearning Algorithms, updated; Cartoon: Surprise #DataScience #Recommendations; DeepLearning in a Nutshell: History and Training; Update: Google #TensorFlow #DeepLearning Is Improving.**Update: Google TensorFlow Deep Learning Is Improving**- Dec 17, 2015.

The recent open sourcing of Google's TensorFlow was a significant event for machine learning. While the original release was lacking in some ways, development continues and improvements are already being made.**Top /r/MachineLearning Posts, November: TensorFlow, Deep Convolutional Generative Adversarial Networks, and lolz**- Dec 2, 2015.

In November on /r/MachineLearning, we've got a good laugh, a fantastic image-generating convolutional generative adversarial network, and a whole lot of Google TensorFlow.**Top KDnuggets tweets, Nov 16-22: Dilbert discovers the perfect chart; TensorFlow Disappoints – Google Deep Learning falls shallow**- Nov 23, 2015.

A standard #graph for any occasion! #Dilbert discovers the perfect chart; TensorFlow Disappoints - Google #DeepLearning falls shallow; All the #BigData tools and how to use them; KDnuggets #DataScience #Cartoon Caption Contest.**KDnuggets™ News 15:n38, Nov 18: TensorFlow Disappoints; Spark with Python; Deep Learning; Top 20 Books**- Nov 18, 2015.

TensorFlow Disappoints - Google Deep Learning falls shallow; Introduction to Spark with Python; A Statistical View of Deep Learning; Amazon Top 20 Books in Databases & Big Data.**Top KDnuggets tweets, Nov 10-16: 5 Books Every #Data Professional Needs; TensorFlow Disappoints – Google Deep Learning falls shallow**- Nov 17, 2015.

Deep Learning for #Visual Question Answering; 5 Books Every #Data Professional Needs; Deep, excellent overview: A Statistical View of #DeepLearning; TensorFlow Disappoints - Google #DeepLearning falls shallow.**TensorFlow Disappoints – Google Deep Learning falls shallow**- Nov 16, 2015.

Google recently open-sourced its TensorFlow machine learning library, which aims to bring large-scale, distributed machine learning and deep learning to everyone. But does it deliver?