Machine Learning Solutions

More Information
  • Select the right algorithm to derive the best solution in ML domains
  • Perform predictive analysis effciently using ML algorithms
  • Predict stock prices using the stock index value
  • Perform customer analytics for an e-commerce platform
  • Build recommendation engines for various domains
  • Build NLP applications for the health domain
  • Build language generation applications using different NLP techniques
  • Build computer vision applications such as facial emotion recognition

Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across in your job.

You’ll encounter a set of simple to complex problems while building ML models, and you'll not only resolve these problems, but you’ll also learn how to build projects based on each problem, with a practical approach and easy-to-follow examples.

The book includes a wide range of applications: from analytics and NLP, to computer vision domains. Some of the applications you will be working on include stock price prediction, a recommendation engine, building a chat-bot, a facial expression recognition system, and many more. The problem examples we cover include identifying the right algorithm for your dataset and use cases, creating and labeling datasets, getting enough clean data to carry out processing, identifying outliers, overftting datasets, hyperparameter tuning, and more. Here, you'll also learn to make more timely and accurate predictions.

In addition, you'll deal with more advanced use cases, such as building a gaming bot, building an extractive summarization tool for medical documents, and you'll also tackle the problems faced while building an ML model. By the end of this book, you'll be able to fine-tune your models as per your needs to deliver maximum productivity.

  • Master the advanced concepts, methodologies, and use cases of machine learning
  • Build ML applications for analytics, NLP and computer vision domains
  • Solve the most common problems in building machine learning models
Page Count 566
Course Length 16 hours 58 minutes
ISBN 9781788390040
Date Of Publication 26 Apr 2018


Jalaj Thanaki

Jalaj Thanaki is an experienced data scientist with a demonstrated history of working in the information technology, publishing, and finance industries. She is author of the book Python Natural Language Processing, Packt publishing.

Her research interest lies in Natural Language Processing, Machine Learning, Deep Learning, and Big Data Analytics. Besides being a data scientist, Jalaj is also a social activist, traveler, and nature-lover.