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Machine Learning With Spark

This Machine Learning With Spark training course teaches attendees how to leverage machine learning at scale with the popular Apache Spark framework. This class dives into foundations, applicability,...

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Duration 3 days
Course Code SPRK-106
Available Formats Classroom

Overview

This Machine Learning With Spark training course teaches attendees how to leverage machine learning at scale with the popular Apache Spark framework. This class dives into foundations, applicability, and limitations, as well as implementation, use, and specific use cases. Students don't just learn the APIs, they learn the theory behind it and work with real-world sample datasets from leading companies.

Skills Gained

  • Learn popular machine learning algorithms, their applicability, and their limitations
  • Practice the application of these methods in the Spark machine learning environment
  • Learn practical use cases and limitations of algorithms
  • Apply ML Concepts
  • Use Regressions, Classifications, and Clustering
  • Perform Principal Component Analysis (PCA)

Prerequisites

This course is intended for data scientists and software engineers, however, we assume no previous knowledge of Machine Learning. Students should have a programming background, and familiarity with Python would be a plus but is not required. If students are new to Apache Spark, we can offer a 1-day Introduction to Spark training primer.

Course Details

Training Materials

All Spark training students receive comprehensive courseware.

Software Requirements

  • Windows, Mac, or Linux PCs with the current Chrome or Firefox browser.
    • Most class activities will create Spark code and visualizations in a browser-based notebook environment. The class also details how to export these notebooks and how to run code outside of this environment.
  • Internet access

Outline

  • Introduction
  • Machine Learning (ML) Overview
    • Machine Learning landscape
    • Machine Learning applications
    • Understanding ML algorithms & models
  • ML in Python and Spark
    • Spark ML Overview
    • Introduction to Jupyter notebooks
  • Machine Learning Concepts
    • Statistics Primer
    • Covariance, Correlation, Covariance Matrix
    • Errors, Residuals
    • Overfitting / Underfitting
    • Cross-validation, bootstrapping
    • Confusion Matrix
    • ROC curve, Area Under Curve (AUC)
  • Feature Engineering (FE)
    • Preparing data for ML
    • Extracting features, enhancing data
    • Data cleanup
    • Visualizing Data
  • Linear regression
    • Simple Linear Regression
    • Multiple Linear Regression
    • Running LR
    • Evaluating LR model performance
    • Use case: House price estimates
  • Logistic Regression
    • Understanding Logistic Regression
    • Calculating Logistic Regression
    • Evaluating model performance
    • Use case: credit card application, college admissions
  • Classification: SVM (Supervised Vector Machines)
    • SVM concepts and theory
    • SVM with kernel
    • Use case: Customer churn data
  • Classification: Decision Trees & Random Forests
    • Theory behind trees
    • Classification and Regression Trees (CART)
    • Random Forest concepts
    • Use case: predicting loan defaults, estimating election contributions
  • Classification: Naive Bayes
    • Theory
    • Use case: spam filtering
  • Clustering (K-Means)
    • Theory behind K-Means
    • Running K-Means algorithm
    • Estimating the performance
    • Use case: grouping cars data, grouping shopping data
  • Principal Component Analysis (PCA)
    • Understanding PCA concepts
    • PCA applications
    • Running a PCA algorithm
    • Evaluating results
    • Use case: analyzing retail shopping data
  • Recommendations (Collaborative filtering)
    • Recommender systems overview
    • Collaborative Filtering concepts
    • Use case: movie recommendations, music recommendations
  • Performance 
    • Best practices for scaling and optimizing Apache Spark
    • Memory caching
    • Testing and validation
  • Conclusion
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Schedule

Upcoming Course Dates

There are currently no scheduled dates for this course. If you are interested in this course, contact us with the form below.

Contact Information

FAQ

Does the course schedule include a Lunchbreak?

Classes typically include a 1-hour lunch break around midday. However, the exact break times and duration can vary depending on the specific class. Your instructor will provide detailed information at the start of the course.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

Does Ascendient Learning deliver group training?

Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.

What does vendor-authorized training mean?

As a vendor-authorized training partner, we offer a curriculum that our partners have vetted. We use the same course materials and facilitate the same labs as our vendor-delivered training. These courses are considered the gold standard and, as such, are priced accordingly.

Is the training too basic, or will you go deep into technology?

It depends on your requirements, your role in your company, and your depth of knowledge. The good news about many of our learning paths, you can start from the fundamentals to highly specialized training.

How up-to-date are your courses and support materials?

We continuously work with our vendors to evaluate and refresh course material to reflect the latest training courses and best practices.

Are your instructors seasoned trainers who have deep knowledge of the training topic?

Ascendient Learning instructors have an average of 27 years of practical IT experience and have also served as consultants for an average of 15 years. To stay current, instructors spend at least 25 percent of their time learning new, emerging technologies and courses.

Do you provide hands-on training and exercises in an actual lab environment?

Lab access is dependent on the vendor and the type of training you sign up for. However, many of our top vendors will provide lab access to students to test and practice. The course description will specify lab access.

Will you customize the training for our company’s specific needs and goals?

We will work with you to identify training needs and areas of growth.  We offer a variety of training methods, such as private group training, on-site of your choice, and virtually. We provide courses and certifications that are aligned with your business goals.

How do I get started with certification?

Getting started on a certification pathway depends on your goals and the vendor you choose to get certified in. Many vendors offer entry-level IT certification to advanced IT certification that can boost your career. To get access to certification vouchers and discounts, please contact info@ascendientlearning.com.

Will I get access to content after I complete a course?

You will get access to the PDF of course books and guides, but access to the recording and slides will depend on the vendor and type of training you receive.

How do I request a W9 for Ascendient Learning?

View our filing status and how to request a W9.

Reviews

the course is good, covers many aspects, wish the lab is a little bit more in depth

I found this course informative. It was easy to follow and provided some good information.

They were very good. They made sure everyone was able to get into the training and got all of the material needed for class.

Some Labs are very good but some steps it ask to update but its already updated, but overall its very good training.

The labs and course material gave me valuable insights into cloud security architecture