Fundamental Machine Learning A-Z : Hands on Python & R in Data Science

DESKRIPSI

This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.

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 OUTLINE

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

PARTICIPANT

1. Anyone interested in Machine Learning.
2. Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
3. Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.

TRAINING METHOD

Pre test

Presentation

Discussion

Case Study

Post test

Evaluation

FACILITIES

Training Kit

Handout

Certificate

Lunch + 2 X Coffee Break

Souvenir

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