Introduction to Machine Learning

PYTH-200 (3 Days)

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Machine Learning Training Overview

Accelebrate's Introduction to Machine Learning training class teaches experienced developers, architects, and team leaders the foundations of building machine learning solutions. Starting with data handling, going through data exploration, and finishing with an algorithms overview, this training provides students with the knowledge of modern tools and the appropriate way of thinking that are crucial for being successful with machine learning.

Note: we offer a free 1-hr pre-recorded Machine Learning with Python Webinar.

Location and Pricing

Most Accelebrate courses are taught as private, customized training for 3 or more attendees at our clients' sites worldwide. In addition, we offer live, private online classes for teams who may be in multiple locations or wish to save on travel costs. Please visit our client list for organizations for whom we have delivered onsite training. To receive a customized proposal and price quote for private on-site or online training, please contact us.

Machine Learning Training Objectives

All students will:

  • Understand what is Machine Learning and which problems does it tackle.
  • Understand the Data Science pipeline.
  • Become familiar with the various tools in the Python ecosystem to handle data (clean and transform).
  • Understand the basics of descriptive statistics and probability for data exploration.
  • Using visualization libraries for gaining insight into the data.
  • Become familiar with using the wide variety of machine-learning algorithms.

Machine Learning Training Outline

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Introduction
The Concepts
  • What is Data Science?
  • The Role of Machine Learning
  • Use-cases
  • Quality of Data
Data Handling
  • Numpy Essentials
  • Introduction to Pandas
  • Working with DataFrames
  • Filtering
  • Vectorized Operations
Descriptive Statistics
  • Measures of Center
  • Measures of Dispersity
  • Correlations
  • Z-Test
  • Pandas and Descriptive Statistics
Visualization
  • Introduction to matplotlib
  • Creating Charts
  • The Seaborn Library
  • Complex Figures
Data Science
  • Introduction to Data Exploration
  • Scaling
  • Feature Selection
  • Feature Engineering
Algorithms Overview
  • Introduction to SKLearn
  • Supervised Learning
  • Regression vs. Classification
  • Overfitting vs. Underfitting
  • Algorithms
    • Linear Regression
    • Logistic Regression
    • Decision Tree (Bagging/RandomForest/GradientBoost)
    • K-Nearest Neighbors
    • Support Vector Machines (SVC/SVR)
  • Introduction to Unsupervised Learning
    • PCA
    • K-Means
Testing and Scoring
  • Overview of Scoring Methods
  • Cross-Validation
Conclusion
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Lecture percentage

50%

Lecture/Demo

Lab percentage

50%

Lab

Course Number:

PYTH-200

Duration:

3 Days

Prerequisites:

No prior knowledge of machine learning, math or data science is required. However, all attendees should know the fundamentals of the Python programming language and feel confident with its syntax.

Training Materials:

All Machine Learning training students receive comprehensive courseware.

Software Requirements:

  • Windows, Mac, or Linux with at least 8 GB RAM
  • Anaconda for Python 3.x
  • Related lab files that Accelebrate will provide

Contact Us:

Accelebrate’s training classes are available for private groups of 3 or more people at your site or online anywhere worldwide.

Don't settle for a "one size fits all" public class! Have Accelebrate deliver exactly the training you want, privately at your site or online, for less than the cost of a public class.

For pricing and to learn more, please contact us.

Contact Us Train For Us

Toll-free in US/Canada:
877 849 1850
International:
+1 678 648 3113

Toll-free in US/Canada:
866 566 1228
International:
+1 404 420 2491

925B Peachtree Street, NE
PMB 378
Atlanta, GA 30309-3918
USA

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