Project on Tensorflow – Implementing Linear Model with Python

These tutorials are entire guide to TensorFlow for Deep Learning with Python.

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 1h 46m | 9 Videos | 55293 Views |   Intermediate

TensorFlow is an open source software library for numerical computation using data flow graphs. These tutorials are entire guide to TensorFlow for Deep Learning with Python. We will help you learn build a neural network and how to train, evaluate and optimize it with TensorFlow

The training will include the following:

1. Tensorflow Installation using Pip and Anaconda Navigator
2. TensorFlow Introduction
3. Environment set up in PyCharm IDE and running Sample Hello World Program
4. Data Types used in TensorFlow and their handling in Python
5. Implementing Linear model example, calculating loss value and reducing loss value using Optimizer and Train
6. Updating existing data element value using Feed Dictionary
7. Placeholder example and Usage and declaration of Constructor
8. Addition of 2 numbers and progammatically calculation of Random numbers

Target Customers:

• Students
• Professionals
• Anyone who wants to learn about Deep Learning Techniques with TensorFlow

Pre-Requisites:

• Basic knowledge of Python programming
• Basic knowledge of math (mean, standard deviation, etc

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