Machine Learning -Workshop

Content of workshops on Machine Learning conducted by TechNeurons

Content Covered

Libraries used: Numpy, Matplotlib, Pandas, Scikit-learn,TensorFlow
Machine Learning Algorithms to be covered:
- Classification :KNN classification and Naive-Bayes Classifier
- Regression: Linear regression and Logistic regression
- Clustering: K-means clustering
- Deep Learning: Simple Neural-Network,CNN,RNN

Day 1 - Overview With Cheatsheets :
- Python Overview
- Library Basics:
  - Numpy
  - Pandas
  - Matplotlib
  - TensorFlow
Day 2 - Data Preprocessing :
- Data Preprocessing with:
  - Scikit-learn
  - Pandas
- Supervised Vs Unsupervised
Day 3/4 - Supervised Learning Methods :
- Supervised method
  1. Classification method
    - Logistic Regression
    - K-Nearest Neighbours(K-NN)
    - Support Vector Mchine(SVM)
    - Kernel SVM
    - Naive Bayes
    - Decision Tree Classification
    - Random Forest Classification
  2. Regression method
    - Simple Linear Regression
    - Multiple Linear Regression
    - Polynomial Regression
    - Support Vector for Regression
    - Decision Tree Regression
    - Random Forest Regression
Day 5 - Unsupervised Learning Methods :
- Clustering Basics
- Clustering Types
- Kmeans Clustering with python code
- A brush-up of different types of clustering
Day 6 - Neural Network/Deep Learning :
- Perceptron
- Activation functions
- Simple ANN using Keras
- CNN
- RNN

Hey There! This is just the start. Stay tuned! :)