Deep Learning - Neural Networks
Overview
Deep learning is a term to describe certain types of neural networks and related algorithms that consume often very raw input data. The process involves sending data through many layers of nonlinear transformations in order to calculate a target output.
Deep learning has been used successfully in many applications, and is considered to be one of the most cutting-edge machine learning and AI techniques. The associated algorithms are often used for supervised, unsupervised, and semi-supervised learning problems.
Neural networks and deep learning provide the best solutions to many problems in image recognition, speech recognition, and natural language processing.
This Repo
In this repository I added a collection of jupyter notebooks with examples of Deep Learning Neural Networks models for classification, regression, image processing and using TensorFlow.
It contains
datasample data used in the modelsnotebooksjupyter notebooks with deep learning models examples
For IMDB Dataset, please, download it here.
For more examples of natural language processing using Tensorflow, please, visit my NLP repo.
This collection of Jupyter Notebooks came from my own studies and trainings I have done during the past years. They are all updated to be used with Python 3.7.
Thank you!