Machine Learning 101 Class Bootcamp Course Intro to AI
What you'll learn
Learn Terms used in Machine Learning in Python 312 285 6886Learn the Basics of Model building without math or programming knowledge
Entry point to Data Science, Machine Learning Career in NYC New York
Requirements
Python 101 (3-10 hours)Data Science 101 (3-10 hours)
Career in Data Science (3-10 hours)
Description
Machine Learning 101 Class Bootcamp Course NYCPython Scikit-learn Library
Supervised vs Unsupervised Learning
Regression vs Classification models
Categorical vs Continuous feature spaces
Modeling Fundamentals: Test-train split, Cross validation(CV), Bias–variance tradeoff, Precision and Recall, Ensemble models
Interpreting Results of Regression and Classification Models (Hands On)
Parameters and Hyper Parameters
SVM, K-Nearest Neighbor, Neural Networks
Dimension Reduction
Hands on:
Understanding and Interpreting results of Regression and Logistic Regression using Google Spreadsheets and Python
Calculating R-Square, MSE, Logit manually in excel for enhanced understanding (Multiple Regression)
Understanding features of Popular Datasets: Titanic, Iris (Scikit) and Housing Prices
Running Logistic Regression on Titanic Data Set
Running Regression, Logistic Regression, SVM and Random Forest on Iris Dataset
Who this course is for:
- Python and Data Analytics
 - Programmers with no knowledge of Maths
 - New Entrants in Data Science Field
 
This course is by Udemy

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