Machine Learning with Code Series 3

Description
Content
Speaker
COURSE OBJECTIVES:
The best way to learn machine learning is by coding. We start the series of workshops to learn machine learning by writing code in python.
Students will follow instructors to implement machine learning algorithms, models, simple applications from scratch through hands on coding labs. And learn about the real word application of different machine learning models with explanation of the necessary principles behind it.
The aim of this workshop is to simplify the inherent concepts of Machine Learning and learn hands-on through building python code and understand applications of the algorithms.
In the second of series, we will learn the following three algorithms:
  • Gradient boosting
  • PCA
  • COURSE SCHEDULE:
    • Session 1: Aug 8th 11am-1pm PST

    COURSE INCLUDE:
    • 2 Hours/ 1 Session
    • Lectures / hands-on code labs
    • Live session and real time interaction
    • Watch session replay anywhere any time

    COURSE CONTENT:
    Check the content tab for full course outlines.

    WHO SHOULD LEARN:
    Developers, data scientists, students.

    PREREQUISITE:
  • Familiarity with Python, or willingness to learn it quickly
  • Basic familiarity with machine learning
  • SESSION REPLAY
    If you miss the live session or want to learn again, you can watch recorded sessions any time, along with interactive learning tools, slides, course notes
    Machine Learning with Code Series 1 - Linear Regression, watch the session replay here

    Module 1: Gradient boosting
  • Introduction
  • Code lab
  • Module 2: PCA
  • Introduction
  • Code lab
  • Anindita Sengupta

    machine learning practitioner, machine learning engineer in residence in AICamp
    • Start Date: On-demand
    • Venue: Online
    • Fee:
      $29 $9
    • Students enrolled:75
    • Status: learn on-demand
    • Preview this course:
    Enroll This Course