Download [Packt] Hands-On Machine Learning with Scala and Spark [FCO] torrent

[Packt] Hands-On Machine Learning with Scala and Spark [FCO]

Torrent:	[Packt] Hands-On Machine Learning with Scala and Spark [FCO]
Description:	By : Tomasz Lelek Released : Wednesday, January 30, 2019 New Release! Torrent Contains : 32 Files, 6 Folders Course Source : https://www.packtpub.com/big-data-and-business-intelligence/hands-machine-learning-scala-and-spark-video Implement machine learning algorithms and evaluate how well they perform with the Scala programming language Video Details ISBN 9781789342468 Course Length 1 hours 41 minutes Table of Contents • ADVANCED TEXT PROCESSING IN SPARK AND BUILDING A CLASSIFICATION MODEL • BUILDING A REGRESSION MODEL WITH SPARK • BUILDING A CLUSTERING MODEL WITH SPARK • DIMENSIONALITY REDUCTIONS AND RECOMMENDATION ENGINES • DEEP LEARNING WITH SPARK Video Description Programmers face multiple challenges while implementing ML; dealing with unstructured data and picking the proper ML model are among the hardest. In this course we will go through day-to-day challenges that programmers face when implementing ML pipelines and consider different approaches and models to solve complex problems. You will learn about the most effective machine learning techniques and implement them in your favor. You will implement algorithms in practical hands-on projects, building data models and understanding how they work by using different types of algorithm. Each section of the course deals with a specific machine learning problem and analysis and gives you insights by using real-world datasets. By the end of this course, you will be able to take huge datasets, extract features from it, and apply a machine learning model that is well suited to your problem. The code bundle for the course is available at: https://github.com/PacktPublishing/Hands-On-Machine-Learning-with-Scala-... Style and Approach This is a step-by-step and fast-paced guide that will help you learn how to create a ML model using the Apache Spark ML toolkit. With this practical approach, you will take your skills to the next level and will be able to create ML pipelines effectively. What You Will Learn • Extract features from data • Write Scala code implementing ML algorithms for prediction and clustering • Analyze the structure of datasets with exploratory data analysis techniques using Scala. • Get to grips with the most popular machine learning algorithms used in the areas of regression, classification, clustering, dimensionality reduction, PCA, and neuralnetworks. • Use the power of MLlib libraries to implement machine learning with Spark • Using GMM to reason about time series data • Work with the k-means and Naive Bayes algorithms and their methods and implement them in Scala with real datasets Authors Tomasz Lelek Tomasz Lelek is a Software Engineer, programming mostly in Java and Scala. He has been working with the Spark and ML APIs 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 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. For More Udemy Free Courses >>> http://www.freetutorials.eu For more Lynda and other Courses >>> https://www.freecoursesonline.me/ Our Forum for discussion >>> https://discuss.freetutorials.eu/
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Show Files »	[FreeCoursesOnline.Me] [Packt] Hands-On Machine Learning with Scala and Spark [FCO] 01.Advanced Text Processing in Spark and Building a Classification Model 0101.The Course Overview.mp4 (19.2 MB) 0102.Analyzing Text Input Data.mp4 (18.9 MB) 0103.Feature Generation from Text – Count Vectorizer, TFIDF, LDA.mp4 (14.1 MB) 0104.Extracting Features from Data – Transforming Text into Vector of Numbers.mp4 (22.7 MB) 0105.Bag-of-Words and Skip Gram.mp4 (8.4 MB) 0106.Training Classification Models – Implementing Word2Vect Using Apache Spark.mp4 (16.3 MB) 02.Building a Regression Model with Spark 0201.Logistic Regression Explanation.mp4 (8.6 MB) 0202.Writing a Logistic Regression Model Per Author in Apache Spark.mp4 (8.6 MB) 0203.Training Regression Model.mp4 (15.3 MB) 0204.Key Concepts, Machine Learning Pipelines, and Operations.mp4 (10.4 MB) 0205.Learn How to Validate Models Using Cross-Validation.mp4 (18.6 MB) 03.Building a Clustering Model with Spark 0301.Analyzing Time of Post Using Clustering – (GMM Explanation).mp4 (6.1 MB) 0302.Implementing GMM in Apache Spark.mp4 (31.5 MB) 0303.K-Means Clustering Explanation and Use Cases.mp4 (4.1 MB) 0304.Implementing K-Means Clustering in Apache Spark.mp4 (18.2 MB) 0305.Measure Accuracy Using Area Under ROC.mp4 (12.6 MB) 04.Dimensionality Reductions and Recommendation Engines 0401.Dimensionality Reduction Using Singular Value Decomposition (SVD).mp4 (14.1 MB) 0402.Building Recommendation Engine in Spark Using Collaborative Filtering.mp4 (18.2 MB) 0403.Using Recommendation Engine to Get Top Recommendations.mp4 (26.3 MB) 0404.Dense and Sparse Vectors.mp4 (13.7 MB) 0405.LabeledPoints, Rating, and Other Data Types.mp4 (10.5 MB) 05.Deep Learning with Spark 0501.The Spark versus Deep Learning Use Case.mp4 (7.7 MB) 0502.Spark for Parallelizing Deep Learning Evaluation.mp4 (15.3 MB) 0503.Deep Learning As a Feature Generator for Existing Spark ML Algorithms.mp4 (11.5 MB) 0504.SparkDeep Learning Made Simple.mp4 (15.2 MB) Exercise Files exercise_files.zip (56.2 KB) Discuss.FreeTutorials.Us.html (165.7 KB) FreeCoursesOnline.Me.html (108.3 KB) FreeTutorials.Eu.html (102.2 KB) How you can help Team-FTU.txt (0.3 KB) [TGx]Downloaded from torrentgalaxy.org.txt (0.5 KB) Torrent Downloaded From GloDls.to.txt (0.1 KB) files
Added:	2019-02-03 11:05:56
Language:	English
Peers:	Seeders : 9 , Leechers : 4
Release name:	[Packt] Hands-On Machine Learning with Scala and Spark [FCO]
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