Data Science and Machine Learning with Java
What you'll 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
- Compare supervised and unsupervised machine learning models and their use cases
- Implement machine learning and deep learning models with real-world data sets
- Split training and testing datasets and determine the accuracy of models using different techniques
- Perform classification using the Weka Library
- Build Regression models for data with multiple features
- Learn how to perform cross-validation
- Implement Natural Language Processing with Deep Learning
Course content
- Preview02:35
- 05:14Environment Configuration — Step 1
- 03:16Environment Configuration — Step 2
- 03:05Environment Configuration — Step 3
- 10:23Loading Data from Different Sources
- 08:14Accessing Different Objects from the Datasets
- 05:33Filtering Unwanted Data
- 10:13Handling the NAN and the Null
- 03:42Formatting Various Data Types
- 06:17Efficient Distribution of Data
- 06:56Correlation in the Data
- 04:13Trend Analysis for Features
- 09:41Visualizing Different Data Forms
- 13:02Using Unsupervised Learning
- 11:13Executing Supervised Learning (Regression)
- 11:26Executing Supervised Learning (Classification)
- 06:53Formatting the Data for Your Model
- 13:18Performing Cross Validation
- 05:34Fitting the Model
- 10:35Predicting and Determining the Accuracy of the Model
- 05:00Importing Deeplearning4j into Your Environment
- 06:36Choosing and Preparing Data for Deep Learning Model
- 08:47Building and Training a Model with a Framework
- 13:17Building and Training a Model Without a Framework
- 5 questionsTest Your Knowledge
Requirements
- Knowledge of Java programming is assumed.
Description
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.
Who this course is for:
- This course is for Java developers who want to perform data science tasks using Java rather than learning any other programming language.
Instructor
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- 57,914 Reviews
- 349,074 Students
- 1,420 Courses
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