Machine Learning with Python
Our Python Development program prepares you for the heavyweight title – Python Developer. Did you know? You can easily clear the Microsoft Certification Exam with our guidance and expert training.
Machine Learning with Python Course content
Course Outline
- Introduction to Machine Learning
- What is ML?
- Applications of ML
- Why ML is the Future
- Types of ML
- Installing Python and Anaconda (MAC & Windows)
- Data Preprocessing
- Importing the Libraries
- Importing the Dataset
- For Python learners, summary of Object-oriented programming: classes & objects
- Missing Data
- Categorical Data
- Splitting the Dataset into the Training set and Test set
- Feature Scaling
- Regression
- Simple Linear Regression
- Dataset + Business Problem Description
- Simple Linear Regression in Python
- Multiple Linear Regression
- Multiple Linear Regression in Python
- Polynomial Regression
- Polynomial Regression in Python
- Support Vector Regression (SVR)
- SVR in Python
- Decision Tree Regression in Python
- Random Forest Regression in Python
- Classification
- Logistic Regression in Python
- K-Nearest Neighbors (K-NN)
- Support Vector Machine (SVM)
- Kernel SVM
- Naive Bayes
- Decision Tree Classification
- Random Forest Classification
- Confusion Matrix
- CAP Curve
- Clustering
- K-Means Clustering in Python
- Hierarchical Clustering in Python
- Association Rule Learning
- Association Rule Learning in Python
- Apriori
- Reinforcement Learning
- Upper Confidence Bound (UCB)
- Thompson Sampling
- Natural Language Processing
- Natural Language Processing in Python
- Deep Learning
- Artificial Neural Networks in Python
- Convolutional Neural Networks in Python
