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[FreeCoursesOnline.Me] [Packt] Hands-On Data Science with Java [FCO]

[FreeCoursesOnline.Me] [Packt] Hands-On Data Science with Java [FCO]

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Description




By: Rahab Wangari

Released: Saturday, March 30, 2019 [New Release!]

Torrent Contains: 31 Files, 6 Folders

Course Source: https://www.packtpub.com/big-data-and-business-intelligence/hands-data-science-java-video



Load, clean, analyze, and visualize your data using Java. Develop Machine Learning and Deep Learning models from scratch



Video Details



ISBN 9781787125346

Course Length 3 hours 5 minutes



Table of Contents



• INTRODUCTION AND SETTING INFRASTRUCTURE

• DATA MANIPULATION AND CLEANING

• DATA INTERACTION AND VISUALIZATION

• IMPLEMENTING ESSENTIAL MACHINE LEARNING ALGORITHMS

• CREATING DEEP LEARNING MODELS WITH DEEP LEARNING



Video Description



Building intensive data science projects is a long and tedious process. Analyzing large data sets requires knowledge of how to deal with all data structures. This means easy access, easier storage, and faster loading. Java provides an efficient way of doing these tasks to improve the efficiency of such data-intensive projects.

In this course, 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'll connect your data with different frameworks, making it easier to analyze small and large data sets. Using the DeepLearning4j library makes training your ML models that much simpler.

By the end of the course, you will be able to build sophisticated and robust data science projects. You will simplify the integration challenges in production using Java. All the code and supporting files for this course are available on GitHub at https://github.com/PacktPublishing/Hands-on-Data-Science-with-Java



Style and Approach



In this hands-on course, the focus is on solving real-world problems. You will start with an introduction to loading data from different sources, and data cleaning, exploration, and visualization. You will implement different machine learning models and build Deep learning models compatible with JVM using Deeplearning4J. To ensure you understand everything from the beginning, we will use familiar data sets in the different scenarios to reduce the time taken to become familiar with the data set.



What You Will Learn



• Perform data science tasks using a set of robust Java tools and libraries

• Develop robust Java code that correctly executes in multiple environments

• Load and analyze data from databases and flat files irrespective of the size and variety of the data

• Clean and filter data and handle null values for data formatting

• Visualize data to understanding 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



Authors



Rahab Wangari



Rahab Wangari is a data science expert with over 4 years' experience in data analytics and software engineering. She is currently a data scientist at Hepta Analytics limited where she oversees the implementation of data analytics projects. She holds a Masters degree in Information Technology with a concentration in Data Science from Carnegie Mellon University and a Bachelor of Science degree in Computer Science (Cum Laude) from Ashesi University College. Her background is in diverse sectors: Academia, Banking, and Manufacturing. Her major interests are in data analytics, machine learning, cyber security management, and software engineering.



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File list
  • [FreeCoursesOnline.Me] [Packt] Hands-On Data Science with Java [FCO]
  • 01.Introduction and Setting Infrastructure/0101.The Course Overview.mp4 25.4 MB
  • 01.Introduction and Setting Infrastructure/0102.Environment Configuration — Step 1.mp4 45.9 MB
  • 01.Introduction and Setting Infrastructure/0103.Environment Configuration — Step 2.mp4 8 MB
  • 01.Introduction and Setting Infrastructure/0104.Environment Configuration — Step 3.mp4 7.5 MB
  • 02.Data Manipulation and Cleaning/0201.Loading the Data from Different Sources.mp4 27.9 MB
  • 02.Data Manipulation and Cleaning/0202.Accessing Different Objects from The Data Sets.mp4 28.3 MB
  • 02.Data Manipulation and Cleaning/0203.Filtering Unwanted Data.mp4 14.1 MB
  • 02.Data Manipulation and Cleaning/0204.Handling the Null and the NAN.mp4 36.7 MB
  • 02.Data Manipulation and Cleaning/0205.Formatting Various Data Types.mp4 8.3 MB
  • 03.Data Interaction and Visualization/0301.Efficient Distribution of The Data.mp4 14.3 MB
  • 03.Data Interaction and Visualization/0302.Correlation in The Data.mp4 16.3 MB
  • 03.Data Interaction and Visualization/0303.Trend Analysis for Features.mp4 7.7 MB
  • 03.Data Interaction and Visualization/0304.Visualizing Different Data Forms.mp4 25 MB
  • 04.Implementing Essential Machine Learning Algorithms/0401.Using Unsupervised Learning.mp4 31.5 MB
  • 04.Implementing Essential Machine Learning Algorithms/0402.Executing Supervised Learning (Regression).mp4 29.5 MB
  • 04.Implementing Essential Machine Learning Algorithms/0403.Executing Supervised Learning (Classification).mp4 25.7 MB
  • 04.Implementing Essential Machine Learning Algorithms/0404.Formatting the Data for Your Model.mp4 23.5 MB
  • 04.Implementing Essential Machine Learning Algorithms/0405.Performing Cross Validation.mp4 41 MB
  • 04.Implementing Essential Machine Learning Algorithms/0406.Fitting the Model.mp4 11.7 MB
  • 04.Implementing Essential Machine Learning Algorithms/0407.Predicting and Determining the Accuracy Of The Model.mp4 22.5 MB
  • 05.Creating Deep Learning Models with Deep Learning/0501.Importing Deep Learning4 Into Your Environment.mp4 61.7 MB
  • 05.Creating Deep Learning Models with Deep Learning/0502.Choosing and Preparing Data for Deep Learning Model.mp4 15.7 MB
  • 05.Creating Deep Learning Models with Deep Learning/0503.Building A Training A Model with A Framework.mp4 22.3 MB
  • 05.Creating Deep Learning Models with Deep Learning/0504.Building and Training A Model Without A Framework.mp4 51.4 MB
  • Discuss.FTUForum.com.html 31.9 KB
  • Exercise Files/exercise_files.zip 1.2 MB
  • FreeCoursesOnline.Me.html 108.3 KB
  • FTUForum.com.html 100.4 KB
  • How you can help Team-FTU.txt 235 B

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