Course Description

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

This course has been developed by professional Data Scientists so that we can provide our knowledge and help you learn complex theories, algorithms, and coding libraries in an easy way.

We will walk you bit by bit into the World of Machine Learning. With each instructional exercise, you will grow new abilities and improve your comprehension of this difficult yet rewarding sub-field of Data Science.

This course is fun and energizing, but at the same time, we analyze Machine Learning. It is organized the accompanying way:

• 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

Additionally, the course is stuffed with reasonable activities that depend on genuine models. So not entirely will you get intimate with the theory, yet you will likewise get a few hands-on works on building your own models.

Also, as a little bit something extra, this course cover both Python and R code layouts which you can download and use on your own tasks.

Significant updates (June 2020):

• CODES ALL UP TO DATE
• DEEP LEARNING CODED IN TENSORFLOW 2.0
• TOP GRADIENT BOOSTING MODELS INCLUDING XGBOOST AND EVEN CATBOOST!

Certification & Includes

• 4 hours on-demand video
• 75 articles
• 38 downloadable resources
• Full lifetime access
• Access on mobile and TV
• Certificate of completion

Who This Course is for

• Anyone interested in Machine Learning.
• Students who have at least high school knowledge in math and who want to start learning Machine Learning.
• 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.
• 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.