- Master Machine Learning on Python & R
- Have a great intuition of many Machine Learning models
- Make accurate predictions
- Create powerful analysis
- Make robust Machine Learning models
- Create strong added value to your business
- Use Machine Learning for personal purpose
- Handle specific topics like Reinforcement Learning, NLP and Deep Learning
- Handle advanced techniques like Dimensionality Reduction
- Know which Machine Learning model to choose for each type of problem
- Build an army of powerful Machine Learning models and know how to combine them to solve any problem
Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Of course code templates included.
Machine Learning A-Z course is fun and exciting, but at the same time we dive deep into Machine Learning. Additionally it is structured the following parts:
- Data Preprocessing;
- Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression also Random Forest Regression;
- Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification;
- Clustering: K-Means, Hierarchical Clustering;
- Association Rule Learning: Apriori, Eclat;
- Reinforcement Learning: Upper Confidence Bound also Thompson Sampling;
- Natural Language Processing: Bag-of-words model and algorithms for NLP;
- Deep Learning: Artificial Neural Networks in addition Convolutional Neural Networks;
- Dimensionality Reduction: PCA, LDA, Kernel PCA;
- Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost.
Moreover, course packed with practical exercises which are based on real-life examples. So not only will you learn the theory, you will also get some hands-on practice building your own models.
After all as a bonus, this course includes both Python and R code templates which you can download and use on your own projects.
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