Top Machine Learning Books And Videos For Beginners And Professionals

Working with real data means that you need to get real insight for your business; don’t let the essential information slip out of your grasp – the world of machine learning awaits you!

Explore Machine Learning with Packt’s range of books and video courses.

Machine Learning For Absolute Beginners [Video] By Eduonix

This best-selling course covers the basic concepts of machine learning that are crucial to get started on the journey of becoming a developer for machine learning.

What You Will Learn:

• Learn core concepts of machine learning
• Learn about different types of machine learning algorithms
• Build real-world projects using supervised and unsupervised learning algorithms
• Learn to implement neural networks

About the author:

Eduonix Learning Solutions – Eduonix creates and distributes high quality technology training content. They have professional team of trainers for technologies ranging from Mobility, Web to Enterprise and Database and Server Administration.

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C# Machine Learning Projects By Yoon Hyup Hwang

This #1 Trending Machine Learning book will help you learn how to choose a model for your problem, how to evaluate the performance of your models, and how you can use C# to build machine learning models for your future projects.

• You will start by setting up your C# environment for machine learning with the required packages, Accord.NET, LiveCharts, and Deedle. We will then take you right from building classifcation models for spam email fltering and applying NLP techniques to Twitter sentiment analysis, to time-series and regression analysis for forecasting foreign exchange rates and house prices, as well as drawing insights on customer segments in e-commerce
• You will then build a recommendation model for music genre recommendation and an image recognition model for handwritten digits
• Lastly, you will learn how to detect anomalies in network and credit card transaction data for cyber-attack and credit card fraud detections
• By the end of this book, you will be putting your skills in practice and implementing your machine learning knowledge in real projects

About the author:

Yoon Hyup Hwang is a seasoned data scientist with several years of experience in marketing and finance industries with expertise in predictive modeling, machine learning, statistical analysis, and data engineering

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Machine Learning with C++ [Video] By Tom Joy

This course takes you through the fundamentals of machine learning, and how you can utilize your C++ skills to build efficient algorithms for predicting and clustering data.

• This course will start off with a broad overview of ML and the varying methods associated with it. You will understand data types, machine learning algorithms, and a simple classification task
• We then study two simple but effective algorithms to deepen your understanding and provide some practical experience. Specifically, the two algorithms that we will be investigating are linear regression and K-means clustering.
• By taking this course, you will be able to get your machine learning basics right and be able to build efficient algorithms which will help you to predict and cluster data

About the author:

Tom Joy is currently working for a SLAM (Simultaneous Localization and Mapping) start-up as a research and development engineer and has extensive experience in computer vision and Machine Learning, having taken several internships and placements over the course of his degree in Engineering Science from the University of Oxford.

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Hands-on Machine Learning with JavaScript By Burak Kanber

This is a practical tutorial that uses hands-on examples to step through some real-world applications of machine learning. Without shying away from the technical details, you will explore machine learning with JavaScript using clear and practical examples.

What You Will Learn:

• Get an overview of state-of-the-art machine learning
• Understand the pre-processing of data handling, cleaning, and preparation
• Learn Mining and Pattern Extraction with JavaScript
• Build your own model for classification, clustering, and prediction
• Identify the most appropriate model for each type of problem
• Apply machine learning techniques to real-world applications
• Learn how JavaScript can be a powerful language for machine learning

About the author:

Burak Kanber is an entrepreneur, software engineer, and the co-author of “Genetic Algorithms in Java”. Currently, Burak is a founder and the CTO of Tidal Labs, a popular enterprise influencer marketing platform.

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