Data Science and Machine Learning with Java




Data Science and Machine Learning with Java

Java is the most used programming language by developers across the world; big data platforms like the Hadoop ecosystem is Java-based, and this presents us to the need for performing data science and artificial intelligence using Java. If you are a Java developer, then this course is your next step on the path to becoming a practitioner in Data Science.

This course teaches you how to perform various data science tasks using Java. You will begin with performing essential tasks such as data cleaning, data manipulation, and data analytics. You will then interact with the data and perform data visualization using various techniques. You will also understand how to select the most appropriate ML algorithms for creating your ML models. Next, you will create deep learning models using the Eclipse Deep Learning 4j Java library. You will learn some of the important concepts for building ML models such as pattern recognition, classification, and regression. Finally, you will implement NLP techniques in building ML and DL models.

Contents and Overview

This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.

In the first course, Hands-On Data Science with Java, you will use efficient Java libraries to simplify your data analysis. You will perform essential tasks such as loading, cleaning, and visualizing your data. You will learn to connect your data with different frameworks, making it easier to analyze small and large data sets. You will also learn to build machine learning models using DeepLearning4j Java library.

In the second course, Machine Learning Projects with Java, you will learn how to build a model that takes complex feature vector form sensor data and classifies data points into classes with similar characteristics. You will then predict the price of a house based on historical data. You will also build a Deep Learning model that can guess personality traits using labeled data.

By the end of this course, you will have a good understanding of the tools and techniques in Java for building your own sophisticated and robust data science projects.

Meet Your Expert(s):

We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:

  • Benson Wachira is an experienced Software Engineer skilled in cloud computing, big data, Azure, AWS, GCP, Java, Python, R, Oracle, Matlab, NoSQL, MySQL, JavaScript, and PHP. He is passionate about manipulating data to gather insights and trends that can be used for decision making. He is a key team player with significant experience in working on collaborative projects and activities, and a strong engineering professional with a Master's degree focused on Data Science and Software Engineering from Carnegie Mellon University. He's also a Co-founder and DevOps Engineer at Hepta Analytics. He has more than 4 years of experience in developing applications in Java. He has also interacted with Hadoop on the cloud to analyze big data using Java.

  • Tomasz Lelek is a Software Engineer and Co-Founder of InitLearn. He mostly does programming in Java and Scala. He dedicates his time and effort to get better at everything. He is currently diving into Big Data technologies. Tomasz is very passionate about everything associated with software development. He has been a speaker at a few conferences in Poland-Confitura and JDD, and at the Krakow Scala User Group. He has also conducted a live coding session at Geecon Conference. He was also a speaker at an international event in Dhaka. He is very enthusiastic and loves to share his knowledge.

Load, clean, analyze, and visualize your data in Java. Develop ML and DL models working on real-world projects

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What you will learn
  • Perform data science tasks using a set of robust Java tools and libraries
  • Load and analyze data from databases and flat files irrespective of the size and variety of the data
  • Visualize data to understand its distribution and discover hidden patterns

Rating: 3.6

Level: Beginner Level

Duration: 5.5 hours

Instructor: Packt Publishing


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