Duration
2 days
What you'll learn
- Master Machine Learning on Python
- Have a great intuition of many Machine Learning models
- Make accurate predictions
- Make powerful analysis
- Make robust Machine Learning models
- Create strong added value to your business
- Use Machine Learning for personal purpose
- Know which Machine Learning model to choose for each type of problem
Who this course is for:
- Anyone interested in Machine Learning.
- Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.
- Any students in college who want to start a career in Data Science.
- Any data analysts who want to level up in Machine Learning.
- Any people who are not satisfied with their job and who want to become a Data Scientist.
- Any people who want to create added value to their business by using powerful Machine Learning tools.
Course Outline
-------------------- Part 1: 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
-------------------- Part 2: Regression --------------------
- Simple Linear Regression
- Multiple Linear Regression
- Polynomial Regression
- Support Vector Regression (SVR)
- Decision Tree Regression
- Random Forest Regression
- Evaluating Regression Models Performance
-------------------- Part 3: Classification --------------------
- Logistic Regression
- K-Nearest Neighbors (K-NN)
- Support Vector Machine (SVM)
- Kernel SVM
- Naive Bayes
- Decision Tree Classification
- Random Forest Classification
- Evaluating Classification Models Performance
-------------------- Part 4: Clustering --------------------
- K-Means Clustering
- Hierarchical Clustering
-------------------- Part 6: Dimensionality Reduction --------------------
- Principal Component Analysis (PCA)
- Linear Discriminant Analysis (LDA)
- Kernel PCA
Programme scope, delivery arrangements and suitability are confirmed during enquiry.