This is the code repository for TensorFlow for Neural Network Solutions [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
TensorFlow is an open source software library for Machine Intelligence. The independent solutions in this video course will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You’ll work through video on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google’s machine learning library TensorFlow.This guide covers important high-level concepts such as neural networks, CNN, RNN, and NLP. Once you are familiar and comfortable with the TensorFlow ecosystem, the last section will show you how to take it to production. Once you are familiar and comfortable with the TensorFlow ecosystem, the last section will show you how to take it to production.
- Learn the math and mechanics of Machine Learning via a developer-friendly approach
- Prepare yourself and other developers for working in the new, ubiquitous field of Machine Learning
- Get an overview of the most well known and powerful tools to solve computing problems using Machine Learning.
- Get an intuitive and down-to-earth introduction
- Apply the concepts to interesting and cutting-edge problems.
To fully benefit from the coverage included in this course, you will need:
Implement neural networks and improve predictions
Apply NLP and sentiment analysis to your data
Master CNN and RNN through practical videos
Take TensorFlow into production
This course has the following software requirements:
The solutions in this course use TensorFlow, which is available at https://www.tensorflow.org/ and are based on Python 3, available at https://www.python.org/downloads/. Most of the solutions will require the use of an Internet connection to download the necessary data.