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ENROLL NOW: Machine Learning & Deep Learning in Python & R
Coupon Code: JULY4AH
COURSE CONTENT
- Introduction
- Setting up Python and Jupyter Notebook
- Setting up R Studio and R crash course
- Basics of Statistics
- Introduction to Machine Learning
- Data Preprocessing
- Linear Regression
- Classification Models: Data Preparation
- The Three classification models
- Logistic Regression
- Linear Discriminant Analysis (LDA)
- K-Nearest Neighbors classifier
- Comparing results from 3 models
- Simple Decision Trees
- Simple Classification Tree
- Ensemble technique 1 – Bagging
- Ensemble technique 2 – Random Forests
- Ensemble technique 3 – Boosting
- Maximum Margin Classifier
- Support Vector Classifier
- Support Vector Machines
- Creating Support Vector Machine Model in Python
- Creating Support Vector Machine Model in R
- Introduction – Deep Learning
- Neural Networks – Stacking cells to create network
- ANN in Python
- ANN in R
- CNN – Basics
- Creating CNN model in Python
- Creating CNN model in R
- Project : Creating CNN model from scratch
- Project : Creating CNN model from scratch
- Project : Data Augmentation for avoiding overfitting
- Transfer Learning : Basics
- Transfer Learning in R
- Time Series Analysis and Forecasting
- Time Series – Preprocessing in Python
- Time Series – Important Concepts
- Time Series – Implementation in Python
- Time Series – ARIMA model
- Time Series – SARIMA model
