YoVDO

Introduction to Machine Learning

Offered By: A Cloud Guru

Tags

Machine Learning Courses Artificial Intelligence Courses Data Science Courses Deep Learning Courses Statistical Analysis Courses Classification Courses Decision Trees Courses

Course Description

Overview

Hello, Cloud Gurus!Have you recently been thrown into your first machine learning project and need to get up to speed? Perhaps you’re struggling with all the mathematical jargon in other machine learning introductory courses?Let machine learning Guru Scott Pletcher guide you through the sometimes intimidating world of machine learning in an entertaining and very non-scary way. Many “introductory” ML courses attempt to explain concepts using differential equations and cryptic Greek symbols–but not this course. This course is specifically designed for people without deep math backgrounds, and Scott cuts through the jargon with simile and metaphor to equip you with concepts and understanding you can put to work immediately.Machine learning has certainly garnered lots of attention in recent years as organizations struggle to remain competitive in the Information Age arms race. Start-ups, established companies, and cloud providers are rapidly releasing new features and services aimed at ML practitioners. Unfortunately, the ability to effectively use these services to create genuine and repeatable business value is somewhat limited by the availability of skilled practitioners. Compounding matters, much of the available ML training in the market presumes a level of advanced mathematics knowledge which can be intimidating to novices.In this course, you’ll learn: Distinction between artificial intelligence, machine learning, data science, and statistical analysis. The various types of machine learning with real-world examples such as regression, classification, decision trees, and deep learning. We’ll even train a self-driving car! How to evaluate and frame business problems for potential machine learning applications. Brief survey of available tools, datasets, and resources common in the machine learning space. Limitations, potential pitfalls, and ethical considerations around machine learning.This is an introductory course so don’t expect to walk away solving math theorems like in Good Will Hunting. However, do expect to come away with much greater machine learning confidence and understanding, pulling back that complexity curtain to unveil how all this modern-day magic really works. (Spoiler alert: it’s really not magic at all…)So Cloud Gurus, let’s take that first step and get started on your machine learning journey.

Syllabus

  • Welcome
  • Back in the Day...
  • The Raw Ingredients
  • "Original Recipe": Supervised and Unsupervised Learning
  • "New and Improved": Reinforcement and Ensemble Learning
  • A New Way of Thinking
  • The Toolbox
  • Unleash the Kraken! Components of an ML Project
  • A Cautionary Tale
  • Look At You Now!

Taught by

Scott Pletcher

Related Courses

Análisis de datos con Python
IBM via Coursera
Análisis de datos empresariales con R
Universidad Anáhuac via Coursera
Analizar e incrementar - Parte 1
Tecnológico de Monterrey via Coursera
Analysis and Interpretation of Large-Scale Programs
Johns Hopkins University via Coursera
Analysis of Variance with ANOVA in Google Sheets
Coursera Project Network via Coursera