By: Arish Ali
Released: Thursday, February 28, 2019 [NEW RELEASE]
Torrent Contains: 34 Files, 7 Folders
Course Source: https://www.packtpub.com/application-development/hands-machine-learning-using-javascript-video

Learn all the CSS Grid concepts and create professional responsive website designs - multiple website layout projects.

Video Details

ISBN 9781789613360
Course Length 2 hours 4 minutes

Table of Contents

• GETTING READY!
• DIVING HEADFIRST INTO SUPERVISED LEARNING
• IMPROVING MODELS
• USING SUPPORT VECTOR MACHINE AND RANDOM FORESTS FOR COMPLEX PROBLEMS
• FINDING HIDDEN VALUE IN UNLABELED DATA
• DEEP NEURAL NETWORKS

Video Description

Machine Learning is a growing and in-demand skill but until now JavaScript developers have not been able to take advantage of it due to the steep learning curve involved in learning a new language. This course shows you various machine learning techniques in a practical way and helps you implement them using the JavaScript language.

Hands-On Machine Learning using JavaScript gives you the opportunity to use the power of machine learning (without installing additional software on the customer's computer) and make them feel safe as the data resides in the system. This course covers basic as well as advanced topics in Machine Learning and gives a holistic picture of the JavaScript machine learning ecosystem by making use of libraries to design smarter applications.

By the end of this course, you'll have gained hands-on experience in evaluating and implementing the right model using the power of JavaScript.

Code files for the course can be found here: https://github.com/PacktPublishing/Hands-On-Machine-Learning-using-JavaScript

Style and Approach

This application-focused course offers practical and actionable guidance with step-by-step instructions, and will enable you to develop your own ML models and methods and use them efficiently in a browser or a Node.js server.

What You Will Learn

• Understanding the machine learning JavaScript ecosystem
• Implement different approaches to problem-solving in machine learning
• Use JavaScript libraries to build neural network models
• Decide, analyze, and make predictions from real-world data
• Use machine learning tools to build models and solve problems
• Use JavaScript to build fun applications in the browser

Authors

Arish Ali

Arish Ali started his machine learning journey 5 years ago by winning an all India machine learning competition conducted by IISC and Microsoft. He was a data scientist at Mu Sigma, one of the biggest analytics firms in India. He has worked on some of the cutting-edge problems of Multi-Touch Attribution Modeling, Market Mix Modeling, and Deep Neural Networks. He has also been an Adjunct faculty for Predictive Business Analytics at Bridge School of Management, which offers its course in Predictive Business Analytics along with Northwestern University (SPS).
He worked at a mental health start-up called Bemo as an AI developer where his role was to help automate the therapy provided to users and make it more personalized. He is currently the CEO at Neurofy Pvt Ltd, a people analytics start-up.

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