Machine Learning Advanced

Interested in the field of Machine Learning? Then this course is for you!

We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

COURSE SYLLABUS:

• Part 1 – Data Preprocessing
• Part 2 – Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
• Part 3 – Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
• Part 4 – Clustering: K-Means, Hierarchical Clustering
• Part 5 – Association Rule Learning: Apriori, Eclat
• Part 6 – Reinforcement Learning: Upper Confidence Bound, Thompson Sampling
• Part 7 – Natural Language Processing: Bag-of-words model and algorithms for NLP
• Part 8 – Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
• Part 9 – Dimensionality Reduction: PCA, LDA, Kernel PCA
• Part 10 – Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost

Moreover, the course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.