Getting Started with NLP and Deep Learning with Python [Video]

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Getting Started with NLP and Deep Learning with Python [Video]

Giuseppe Bonaccorso

Build a strong foundation to enter the world of Machine Learning and data science with the help of this comprehensive guide
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Video Details

ISBN 139781789138894
Course Length1 hour and 41 minutes

Video Description

As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine Learning applications are everywhere, from self-driving cars to spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge.

In this course, you’ll be introduced to the Natural Processing Language and Recommendation Systems, which help you run multiple algorithms simultaneously. Also, you’ll learn about Deep learning and TensorFlow. Finally, you’ll see how to create an Ml architecture.

Style and Approach

An easy-to-follow, step-by-step guide that will help you get to grips with real-world applications of algorithms for Machine Learning.

Table of Contents

Introduction to Natural Language Processing
The Corse Overview
NLTK and Built-In Corpora
The Bag-Of-Words Strategy
A Sample Text Classifier
Topic Modeling and Sentiment Analysis in NLP
Latent Semantic Analysis
Probabilistic Latent Semantic Analysis
Latent Dirichlet Allocation
Introduction to Deep Learning and TensorFlow
Deep Learning at a Glance
Introduction to TensorFlow
A Quick Glimpse Inside Keras
Deep Learning at a Glance
Creating a Machine Learning Architecture
Machine Learning Architecture
Scikit-learn Tools for Machine Learning Architectures

What You Will Learn

  • Explore the concept of Natural Processing Language and Recommendation Systems
  • Tokenize a sentence
  • Transform text tokens into numerical vectors by vectorizing
  • Modeling topics to identify common topics among documents
  • Find out about ANNs
  • Compute the gradients of all output tensors
  • Create a Machine Learning architecture from scratch

Authors

Table of Contents

Introduction to Natural Language Processing
The Corse Overview
NLTK and Built-In Corpora
The Bag-Of-Words Strategy
A Sample Text Classifier
Topic Modeling and Sentiment Analysis in NLP
Latent Semantic Analysis
Probabilistic Latent Semantic Analysis
Latent Dirichlet Allocation
Introduction to Deep Learning and TensorFlow
Deep Learning at a Glance
Introduction to TensorFlow
A Quick Glimpse Inside Keras
Deep Learning at a Glance
Creating a Machine Learning Architecture
Machine Learning Architecture
Scikit-learn Tools for Machine Learning Architectures

Video Details

ISBN 139781789138894
Course Length1 hour and 41 minutes
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