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Thursday, October 11, 2018

Codecademy - Machine Learning Fundamentals - Syllabus

Upgrade your skills with Codecademy's Pro Intensive, Machine Learning Fundamentals.
Each unit will cover conceptual and syntax lessons and quizzes. There will also be a few cumulative off-platform projects throughout the Intensive. Articles and videos will be available to supplement your learning.
Unit 1- What is Machine Learning?
Learn about the types of problems to solve with machine learning.
Machine Learning Process
Learn about Scikit
Why Data?
Unit 2 - Regression
Predict continuous-valued output based on the input value(s).
Distance Formula
Linear Regression
Multiple Linear Regression
Precision vs Recall
Unit 3 - Classification
Classify data into different categories.
Bayes’ Theorem
Naive Bayes Classifier
K-Nearest Neighbors
The Ethics of Overfitting
Unit 4 - Unsupervised Learning
Find patterns and structures in unlabeled data points.
K-Means Clustering
K-Means++ Clustering
Unit 5 - Neural Network Teaser
Implement a single neuron - the building block of neural networks.
Perceptron
Unit 6 - Capstone Project
Apply your new knowledge to complex projects reviewed by experts.
Yelp recommender
Date-a-Scientist

Machine Learning Workflow

Data cleaning Missing data Outlier Others: duplicates, typos, special characters Strategy for missing data: imputation, mean, median...