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

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[Packt] Hands-On Machine Learning with Scala and Spark [FCO] (Size: 366.6 MB)
  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
  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
  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
  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
  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
  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 307.2 B
  Torrent Downloaded From GloDls.to.txt 102.4 B
  [TGx]Downloaded from torrentgalaxy.org.txt 512 B
  exercise_files.zip 56.2 KB
  ▲ 32 total files

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.

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