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TORRENT DETAILS

[FreeCoursesOnline.Me] [Packt] Machine Learning Projects With Java [FCO]

TORRENT SUMMARY

	Status:	All the torrents in this section have been verified by our verification system
Category:	Other
Infohash	3d5ac8bd3d049ce74e8488561ddf8c5271c45c83
Size:	630.1 MB in 28 files
Release Date(s):	Torrent Release: 04-04-2019 by user
Swarm:	0 Seeds & 0 Peers
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DESCRIPTION

By: Tomasz Lelek

Released: Friday, March 29, 2019 [New Release!]

Torrent Contains: 30 Files, 5 Folders

Course Source: https://www.packtpub.com/big-data-and-business-intelligence/machine-learning-projects-java-video

Learn how to leverage well-proven ML algorithms to solve day-to-day ML problems

Video Details

ISBN 9781789612455

Course Length 2 hour 12 minutes

Table of Contents

• FEATURE EXTRACTION FOR UNSTRUCTURED TEXTUAL NEWS FEED DATA

• ML CLASSIFICATION FOR PATTERN RECOGNITION OF SENSOR DATA USING WEKA LIBRARY

• BUILDING REGRESSION MODEL FOR HOUSING MARKET

• DEEP LEARNING FOR PREDICTING GENDER BASED ON THE NAME

• FINDING SIMILARITY OF WORDS IN A BOOK USING NLP WITH DEEP LEARNING

Video Description

Developers are worried about using various algorithms to solve different problems. This course is a perfect guide to identifying the best solution to efficiently build machine learning projects for different use cases to solve real-world problems.

In this course, 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. Then you will predict the price of a house based on historical data. Finally, you will build a Deep Learning model that can guess personality traits using labeled data.

By the end of this course, you will have mastered each machine learning domain and will be able to build your own powerful projects at work.

Style and Approach

This is a step-by-step and fast-paced guide that will help you learn different ML techniques you can use to solve real-world problems, Every section will tackle a practical problem and take your ML skills to the next level

What You Will Learn

• Perform classification using the Weka Library.

• Implement Pattern Recognition of non-labeled data

• Build Regression models for data with multiple features

• Save trained models for further reusability

• Learn how to perform cross-validation

• Leverage Deep Learning in ML problems

• Implement Natural Language Processing with Deep Learning

Authors

Tomasz Lelek

Tomasz Lelek is a Software Engineer, programming mostly in Java, Scala. He has worked with ML algorithms for the past 5 years, with production experience in processing petabytes of data.

He is passionate about nearly everything associated with software development and believes that we should always try to consider different solutions and approaches before solving a problem. Recently he was a speaker at conferences in Poland, Confitura and JDD (Java Developers Day), and also at Krakow Scala User Group. He has also conducted a live coding session at Geecon Conference.

He is a co-founder of www.initlearn.com, an e-learning platform that was built with the Java language.

He has also written articles about everything related to the Java world: http://www.baeldung.com/.

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FILE LIST

Filename		Size
	1. FEATURE EXTRACTION FOR UNSTRUCTURED TEXTUAL NEWS FEED DATA/1. The Course Overview.MP4	24.4 MB
	1. FEATURE EXTRACTION FOR UNSTRUCTURED TEXTUAL NEWS FEED DATA/2. Performing Feature Engineering.MP4	40.9 MB
	1. FEATURE EXTRACTION FOR UNSTRUCTURED TEXTUAL NEWS FEED DATA/3. Leveraging ND4J Library Input Vectors and Matrices.MP4	18.7 MB
	1. FEATURE EXTRACTION FOR UNSTRUCTURED TEXTUAL NEWS FEED DATA/4. Extracting INDArray Features.MP4	22.6 MB
	1. FEATURE EXTRACTION FOR UNSTRUCTURED TEXTUAL NEWS FEED DATA/5. Applying Scalar Transformations to Features Vectors.MP4	26.9 MB
	2. ML CLASSIFICATION FOR PATTERN RECOGNITION OF SENSOR DATA USING WEKA LIBRARY/1. Project Set Up Using Weka Library.MP4	26.2 MB
	2. ML CLASSIFICATION FOR PATTERN RECOGNITION OF SENSOR DATA USING WEKA LIBRARY/2. Data Mining of Input Data Set.MP4	15.6 MB
	2. ML CLASSIFICATION FOR PATTERN RECOGNITION OF SENSOR DATA USING WEKA LIBRARY/3. Building Classifier in Weka Library.MP4	19.5 MB
	2. ML CLASSIFICATION FOR PATTERN RECOGNITION OF SENSOR DATA USING WEKA LIBRARY/4. Performing Cross-Validation of the Model.MP4	13.9 MB
	2. ML CLASSIFICATION FOR PATTERN RECOGNITION OF SENSOR DATA USING WEKA LIBRARY/5. Making Predictions Based on the Classification.MP4	22 MB
	3. BUILDING REGRESSION MODEL FOR HOUSING MARKET/1. Extracting Feature Vector for Housing Data.MP4	19.7 MB
	3. BUILDING REGRESSION MODEL FOR HOUSING MARKET/2. Performing Normalization of Data.MP4	20 MB
	3. BUILDING REGRESSION MODEL FOR HOUSING MARKET/3. Building Regression Model.MP4	17.1 MB
	3. BUILDING REGRESSION MODEL FOR HOUSING MARKET/4. Leveraging Regression Model for Predicting Price of House.MP4	22.7 MB
	3. BUILDING REGRESSION MODEL FOR HOUSING MARKET/5. Saving Model for Further Re-Usage.MP4	16.5 MB
	4. DEEP LEARNING FOR PREDICTING GENDER BASED ON THE NAME/1. Feeding DL4J Model with Gender Labeled Data.MP4	16.9 MB
	4. DEEP LEARNING FOR PREDICTING GENDER BASED ON THE NAME/2. Creating a .java File for Automatic Feature Extraction.MP4	21.4 MB
	4. DEEP LEARNING FOR PREDICTING GENDER BASED ON THE NAME/3. Creating Neural Network with Multiple Layers.MP4	21.9 MB
	4. DEEP LEARNING FOR PREDICTING GENDER BASED ON THE NAME/4. Training of Deep Learning Model.MP4	22 MB
	4. DEEP LEARNING FOR PREDICTING GENDER BASED ON THE NAME/5. Performing Validation of a Model.MP4	29.9 MB
	5. FINDING SIMILARITY OF WORDS IN A BOOK USING NLP WITH DEEP LEARNING/1. Extracting Feature Vector from Text Data.MP4	25.1 MB
	5. FINDING SIMILARITY OF WORDS IN A BOOK USING NLP WITH DEEP LEARNING/2. Loading Raw Data That will be an Input for NLP Training.MP4	17.8 MB
	5. FINDING SIMILARITY OF WORDS IN A BOOK USING NLP WITH DEEP LEARNING/3. Leveraging NLP Construct from DL4J.MP4	69.1 MB
	5. FINDING SIMILARITY OF WORDS IN A BOOK USING NLP WITH DEEP LEARNING/4. Finding Words Based on the Similarity.MP4	79 MB
	Discuss.FTUForum.com.html	31.9 KB
	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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