Machine Learning Fundamentals with Python Training Course

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Course CodeCourse Code

mlfunpython

Duration Duration

14 hours (usually 2 days including breaks)

Requirements Requirements

Knowledge of Python programming language. Basic familiarity with statistics and linear algebra is recommended.

Overview Overview

The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results.

Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.

Course OutlineCourse Outline

Introduction to Applied Machine Learning

  • Statistical learning vs. Machine learning
  • Iteration and evaluation
  • Bias-Variance trade-off

Machine Learning with Python

  • Choice of libraries
  • Add-on tools

Regression

  • Linear regression
  • Generalizations and Nonlinearity
  • Exercises

Classification

  • Bayesian refresher
  • Naive Bayes
  • Logistic regression
  • K-Nearest neighbors
  • Exercises

Cross-validation and Resampling

  • Cross-validation approaches
  • Bootstrap
  • Exercises

Unsupervised Learning

  • K-means clustering
  • Examples
  • Challenges of unsupervised learning and beyond K-means

Bookings, Prices and EnquiriesBookings, Prices and Enquiries

Private Classroom
 
Private Classroom
Participants are from one organisation only. No external participants are allowed. Usually customised to a specific group, course topics are agreed between the client and the trainer.
Private Remote
From 1490EUR
Private Remote
The instructor and the participants are in two different physical locations and communicate via the Internet. More Information

The more delegates, the greater the savings per delegate. Table reflects price per delegate and is used for illustration purposes only, actual prices may differ.

Number of Delegates Private Remote
1 1490EUR
2 950EUR
3 770EUR
4 680EUR
Public Classroom
From 1990EUR
(208)
Public Classroom
Participants from multiple organisations. Topics usually cannot be customised

The more delegates, the greater the savings per delegate. Table reflects price per delegate and is used for illustration purposes only, actual prices may differ.

Number of Delegates Public Classroom
1 1990EUR
2 1225EUR
3 970EUR
4 843EUR
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Upco...Upcoming Courses

VenueCourse DateCourse Price [Remote / Classroom]
BaselMon, 2017-11-06 09:301490EUR / 1990EUR
ZürichMon, 2017-11-06 09:301490EUR / 1990EUR
BernTue, 2017-11-07 09:301490EUR / 1990EUR

Course Discounts

Course Venue Course Date Course Price [Remote / Classroom]
MongoDB for Developers Zürich Mon, 2017-11-06 09:30 1782EUR / 2282EUR
Statistics Level 1 Bern Wed, 2017-11-15 09:30 1881EUR / 2381EUR
Neural Network in R Zürich Tue, 2017-11-21 09:30 1872EUR / 2372EUR
Semantic Web Overview Zürich Wed, 2017-11-29 09:30 972EUR / 1322EUR
Drools Rules Administration Bern Wed, 2018-02-28 09:30 2961EUR / 3611EUR

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