What is the Best TensorFlow Tutorial?
POPULAR | Complete Guide to TensorFlow for Deep Learning with Python The most popular TensorFlow tutorial with over 58,500 students and 14 hours of video! You will learn all about Neural Networks and their different kinds and how to use TensorFlow. | |
COMPREHENSIVE | Master Deep Learning with TensorFlow in Python You will learn to master TensorFlow in this tutorial. TensorFlow and NumPy are explored in-depth. You will learn to build your own Deep Learning algorithms in an hour! This course has over 7,000 students and 6 hours of video. | |
ADVANCED | Tensorflow Bootcamp For Data Science in Python Learn Data Science with TensorFlow. You will llearn Jupyter, Pandas, NumPy and more! Runtime is 7.5 hours of video. |
What is the Best TensorFlow Book?
Best TensorFlow tutorials 2019
Popular
Complete Guide to TensorFlow for Deep Learning with Python
Complete Guide to TensorFlow for Deep Learning with Python by Jose Portilla will help you learn TensorFlow, Google’s Deep Learning Framework. This TensorFlow course is for Python developers who want to learn the latest Deep Learning techniques with TensorFlow.
You will learn:
- Neural Network Basics
- TensorFlow Basics
- Artificial Neural Networks
- Densely Connected Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- AutoEncoders
- Reinforcement Learning
- OpenAI Gym
You will understand how Neural Networks work and build your own Neural Network from scratch with Python. This TensorFlow tutorial will teach you to use TensorFlow for Classification and Regression Tasks. You will make further use of TensorFlow for Image Classification with Convolutional Neural Networks, Time Series Analysis with Recurrent Neural Networks and solving Unsupervised Learning Problems with AutoEncoders. This TensorFlow and Python course will help you learn how to conduct Reinforcement Learning with OpenAI Gym. You will be able to create Generative Adversarial Networks using TensorFlow.
This is one of the best TensorFlow tutorials in 2019.
Machine Learning with TensorFlow for Business Intelligence
Machine Learning with TensorFlow for Business Intelligence by 365 Careers will help you learn how to build Deep Learning algorithms with TensorFlow. This TensorFlow tutorial will teach you to create Deep Learning algorithms from scratch in Python, using NumPy and TensorFlow. You will begin with NumPy and transfer to TensorFlow, to see the Machine Learning process from different angles.
This TensorFlow tutorial will move onto more complex topics including underfitting and overfitting, training, validation, n-fold cross-validation, testing, early stopping, initialization. You will learn all about optimization techniques like the stochastic gradient descent, batching, momentum, and learning rate schedules. This TensorFlow course will teach you to carry out preprocessing – standardization, normalization, and one-hot encoding.
You will learn:
- TensorFlow and NumPy, two tools essential for creating and understanding Deep Learning algorithms.
- Explore layers, their building blocks and activations – sigmoid, tanh, ReLu, softmax, etc.
- Backpropagation process, intuitively and mathematically.
- Spot and prevent overfitting.
- State-of-the-art initialization methods.
- Build deep neural networks using real data, implemented by real companies in the real world.
- Create your very own Deep Learning Algorithm.
- Gain hands-on TensorFlow experience.
This is one of the best TensorFlow courses in 2019.
TensorFlow 101: Introduction to Deep Learning
TensorFlow 101: Introduction to Deep Learning by Sefik Ilkin Serengil will help you learn how to build Deep Learning models for different business domains in TensorFlow. This TensorFlow course is for anyone who wants to learn TensorFlow framework. If you are interested in Machine Learning, Data Science or AI, you should check out this TensorFlow course. You will be able to distinguish classification and regression problems, apply supervised learning, and develop solutions. This TensorFlow tutorial will teach you to apply segmentation analysis to unsupervised learning and clustering. You will learn how to use TensorFlow via Keras. By the end of the course, you will know how to tune Machine Learning models to produce more successful results.
TensorFlow and the Google Cloud ML Engine for Deep Learning
TensorFlow and the Google Cloud ML Engine for Deep Learning by Loony Corn is a comprehensive TensorFlow tutorial. This TensorFlow tutorial starts at TensorFlow basics. You will learn to build and execute machine learning models using TensorFlow. This TensorFlow course will teach you to implement Deep Neural Networks, Convolutional Neural Networks and Recurrent Neural Networks. You will understand and implement unsupervised learning models such as Clustering and Autoencoders.
You will learn:
- Deep learning basics including what a neuron is, how neural networks connect neurons to ‘learn’ complex functions and how TF makes it easy to build neural network models.
- Using Deep Learning for the famous ML problems inclduing regression, classification, clustering and autoencoding.
- Convolutional Neural Networks(CNNs) including Kernel functions, feature maps and CNNs v DNNs.
- Recurrent Neural Networks(RNNs) including LSTMs, Back-propagation through time and dealing with vanishing/exploding gradients.
- Unsupervised learning techniques including Autoencoding, K-means clustering, PCA as autoencoding .
- Working with images, documents and word embeddings
- Google Cloud ML Engine including Distributed training and prediction of TF models on the cloud.
- Working with TensorFlow estimators.
This is one of the best TensorFlow tutorials for Deep Learning.
Tensorflow Bootcamp For Data Science in Python
Tensorflow Bootcamp For Data Science in Python by Minerva Singh will help you learn TensorFlow for Machine Learning & Deep Learning. You will use Anaconda/iPython for Data Science. This TensorFlow tutorial will help you learn how to install and use Tensorflow with Anaconda. You will implement statistical and Machine Learning, Neural Network Modelling, Deep Learning based unsupervised learning and Deep Learning based supervised learning.
This TensorFlow tutorial covers:
- Introduction to Python Data Science
- Introduction to Anaconda
- Jupyter notebooks for implementing data science techniques in Python
- Comprehensive guide to Tensorflow installation
- Introduction to Python data science packages
- Introduction to Pandas and Numpy
- Basics of the Tensorflow syntax and graphing environment
- Statistical modelling
- Machine Learning, Supervised Learning, Unsupervised Learning in the Tensorflow framework
- Create artificial neural networks and deep learning structures
This is one of the best TensorFlow bootcamps in 2019.
Best TensorFlow books 2019
Bestsellers
- O Reilly Media
- Aurélien Géron
- Publisher: O'Reilly Media
- Edition no. 1 (04/09/2017)
- Paperback: 574 pages
- Aurélien Géron
- Publisher: O'Reilly Media
- Edition no. 2 (10/06/2019)
- Paperback: 838 pages
- Julian Avila, Trent Hauck
- Packt Publishing
- Kindle Edition
- Edition no. 2 (11/16/2017)
- English
- Benjamin Planche, Eliot Andres
- Publisher: Packt Publishing
- Paperback: 372 pages
- Bharath Ramsundar, Reza Bosagh Zadeh
- Publisher: O'Reilly Media
- Edition no. 1 (03/23/2018)
- Paperback: 256 pages
- Antonio Gulli, Amita Kapoor
- Publisher: Packt Publishing
- Paperback: 536 pages
- Sebastian Raschka, Vahid Mirjalili
- Publisher: Packt Publishing
- Edition no. 2 (09/20/2017)
- Paperback: 622 pages
- Samuel Burns
- Publisher: Independently published
- Paperback: 170 pages
- Nishant Shukla
- Publisher: Manning Publications
- Edition no. 1 (02/12/2018)
- Paperback: 272 pages
- Ankit Jain, Armando Fandango, Amita Kapoor
- Publisher: Packt Publishing
- Paperback: 322 pages
Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras
- Armando Fandango
- Publisher: Packt Publishing - ebooks Account
- Paperback: 474 pages
Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras
by Armando Fandango will help you learn and master TensorFlow. You will learn to build, scale, and deploy deep neural network models with TensorFlow. This TensorFlow book will help you deploy TensorFlow on mobile, and distributed TensorFlow on GPU, Clusters, and Kubernetes. You will delve into advanced machine learning and deep learning use cases making use of Tensorflow and Keras.
This TensorFlow book will help you learn:
- Master advanced Deep Learning concepts including transfer learning, reinforcement learning, generative models and more, using TensorFlow and Keras
- Perform supervised (classification and regression) and unsupervised (clustering) learning to solve machine learning tasks
- Build end-to-end deep learning (CNN, RNN, and Autoencoders) models with TensorFlow
- Scale and deploy production models with distributed and high-performance computing on GPU and clusters
- Build TensorFlow models to work with multilayer perceptrons using Keras, TFLearn, and R
- Learn smart app functionalities by building and deploying TensorFlow models on iOS and Android devices
- Supercharge TensorFlow with distributed training and deployment on Kubernetes and TensorFlow Clusters
This is one of the best TensorFlow books in 2019.
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
- O Reilly Media
- Aurélien Géron
- Publisher: O'Reilly Media
- Edition no. 1 (04/09/2017)
- Paperback: 574 pages
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron will help you learn
deep learning with TensorFlow and Scikit-Learn. This TensorFlow book will teach you a range of techniques, starting with simple linear regression and progressing to deep neural networks. You will learn from exercises, examples and minimal theory.
This TensorFlow book will help you:
- Explore machine learning, including neural nets
- Use scikit-learn to track an example machine-learning project
- Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods
- Use the TensorFlow library to build and train neural nets
- Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning
- Learn techniques for training and scaling deep neural nets
- Apply practical code examples without acquiring excessive machine learning theory or algorithm details
This is one of the best TensorFlow books in 2019.
Learning TensorFlow: A Guide to Building Deep Learning Systems
- OREILLY
- Tom Hope, Yehezkel S. Resheff, Itay Lieder
- Publisher: O'Reilly Media
- Edition no. 1 (08/27/2017)
- Paperback: 242 pages
Learning TensorFlow: A Guide to Building Deep Learning Systems by Tom Hope, Yehezkel S. Resheff and Itay Lieder gives a hands-on approach to TensorFlow fundamentals.
Machine Learning with TensorFlow
- Nishant Shukla
- Publisher: Manning Publications
- Edition no. 1 (02/12/2018)
- Paperback: 272 pages
>Machine Learning with TensorFlow by Nishant Shukla will give you a solid foundation in machine-learning concepts with hands-on experience coding TensorFlow with Python. This TensorFlow book will teach you how to use TensorFlow for machine-learning and building deep-learning applications.
Pro Deep Learning with TensorFlow: A Mathematical Approach to Advanced Artificial Intelligence in Python
- Santanu Pattanayak
- Publisher: Apress
- Edition no. 1 (12/07/2017)
- Paperback: 424 pages
Pro Deep Learning with TensorFlow: A Mathematical Approach to Advanced Artificial Intelligence in Python by Santanu Pattanayak gives you a practical and hands-on guide to learn deep learning from scratch with TensorFlow. This TensorFlow book will get you up to speed quickly using TensorFlow and teach you to optimize different deep learning architectures.
Last update on 2019-08-16 / Affiliate links / Images from Amazon Product Advertising API