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Learn Machine Learning 101 Class Bootcamp Course NYC

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Publisher : Shivgan Joshi

Course Language : English

Machine Learning 101 Class Bootcamp Course NYC

  1. Python Scikit-learn Library

  2. Supervised vs Unsupervised Learning

  3. Regression vs Classification models

  4. Categorical vs Continuous feature spaces

  5. Modeling Fundamentals: Test-train split, Cross validation(CV), Bias–variance tradeoff, Precision and Recall, Ensemble models

  6. Interpreting Results of Regression and  Classification Models (Hands On)

  7. Parameters and Hyper Parameters

  8. SVM, K-Nearest Neighbor, Neural Networks

  9. Dimension Reduction

Hands on:

  1. Understanding and Interpreting results of Regression and Logistic Regression using Google Spreadsheets and Python

  2. Calculating R-Square, MSE, Logit manually in excel for enhanced understanding (Multiple Regression)

  3. Understanding features of Popular Datasets: Titanic, Iris (Scikit) and Housing Prices

  4. Running Logistic Regression on Titanic Data Set

  5. Running Regression, Logistic Regression, SVM and Random Forest on Iris Dataset