Machine Learning A-Z: Hands-On Python and R In Data Science

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Course Description

Interested in the field of Machine Learning? Then this course is for you!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.This course is fun and exciting, but at the same time we dive deep into Machine Learning. It is structured the following way:Part 1 - Data PreprocessingPart 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest RegressionPart 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest ClassificationPart 4 - Clustering: K-Means, Hierarchical ClusteringPart 5 - Association Rule Learning: Apriori, EclatPart 6 - Reinforcement Learning: Upper Confidence Bound, Thompson SamplingPart 7 - Natural Language Processing: Bag-of-words model and algorithms for NLPPart 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural NetworksPart 9 - Dimensionality Reduction: PCA, LDA, Kernel PCAPart 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoostMoreover, 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.And 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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