This TensorFlow tutorial for beginners covers TensorFlow basics to advance topics like linear regression, classifier, create, train and evaluate a neural network like CNN, RNN, auto encoders etc with TensorFlow examples. Refer this Machine Learning TensorFlow tutorial, sequentially, one after the other, for maximum efficacy to learn TensorFlow. Learn Tensorflow basic concepts with this TensorFlow Deep Learning tutorial.

What is TensorFlow?

Google's TensorFlow is an open-source and most popular deep learning library for research and production. TensorFlow in Python is a symbolic math library that uses dataflow and differentiable programming to perform various tasks focused on training and inference of deep neural networks.

Course Syllabus

Introduction
Tutorial What is TensorFlow? How it Works? Introduction & Architecture
Tutorial How to Download and Install TensorFLow Windows and Mac
Tutorial Jupyter Notebook Tutorial: How to Install & Use Jupyter?
Tutorial TensorFlow Basics: Tensor, Shape, Type, Sessions & Operators
Advanced Stuff
Tutorial Tensorboard Tutorial: Graph Visualization with Example
Tutorial Python Pandas Tutorial: DataFrame, Date Range, Use of Pandas
Tutorial Import CSV Data using Pandas.read_csv()
Tutorial Linear Regression with TensorFlow [Examples]
Tutorial TensorFlow Linear Regression with Facet & Interaction Term
Tutorial Binary Classification in TensorFlow: Linear Classifier Example
Tutorial Gaussian Kernel in Machine Learning: Kernel Methods Examples
Tutorial Artificial Neural Network (ANN): TensorFlow Example Tutorial
Tutorial TensorFlow Image Classification: CNN (Convolutional Neural Network)
Tutorial TensorFlow Autoencoder: Dataset with Deep Learning Example
Tutorial RNN (Recurrent Neural Network) Tutorial: TensorFlow Example
Tutorial PySpark Tutorial for Beginners: Learn with EXAMPLES
Tutorial Scikit-Learn Tutorial: How to Install, Python Scikit-Learn Example
Must Know!
Tutorial 10 BEST TensorFlow Books
Tutorial TensorFlow Tutorial PDF

What will I learn in this TensorFlow Tutorial?

In this TensorFlow 2.0 tutorial, you will learn basic and advanced concepts of TensorFlow like TensorFlow introduction, architecture, how to download and install TensorFlow, TensorBoard, Python Pandas, Linear regression, Kernel Methods, Neural Networks, Autoencoder, RNN, etc.

Are there any prerequisites for this TensorFlow Tutorial?

This online Tensorflow Python Tutorial is designed for beginners with little or no TensorFlow Experience. Though basic understanding of Python is required.

Who is this TensorFlow Tutorial for?

This TensorFlow Deep Learning Tutorial is for beginners who want to gain knowledge about TensorFlow, Machine Learning, Deep Learning, and more advanced concepts. This tutorial also helps Python developers for research and development purposes in Machine Learning and Deep Learning with TensorFlow using Python.

Why should you learn TensorFlow?

TensorFlow is a widely preferred framework for Machine Learning and Deep Learning applications, and it also allows building a strong foundation for Deep learning. Moreover, it is widely used by many big companies worldwide, so there is a vast number of job opportunities available for candidates with better salary prospects. Therefore, learning TensorFlow to either get a job or gain additional knowledge is beneficial for a candidate.