Are you ready to master Machine Learning techniques and Kick-off your career as a Data Scientist?!
You came to the right place!
Machine Learning skill is one of the top skills to acquire in 2019 with an average salary of over $114,000 in the United States according to PayScale! The total number of ML jobs over the past two years has grown around 600 percent and expected to grow even more by 2020.
This course provides students with knowledge, hands-on experience of state-of-the-art machine learning classification techniques such as
- Logistic Regression
- Decision Trees
- Random Forest
- Naïve Bayes
- Support Vector Machines (SVM)
In this course, we are going to provide students with knowledge of key aspects of state-of-the-art classification techniques. We are going to build 10 projects from scratch using real world dataset, here’s a sample of the projects we will be working on:
- Build an e-mail spam classifier.
- Perform sentiment analysis and analyze customer reviews for Amazon Alexa products.
- Predict the survival rates of the titanic based on the passenger features.
- Predict customer behavior towards targeted marketing ads on Facebook.
- Predicting bank client’s eligibility to retire given their features such as age and 401K savings.
- Predict cancer and Kyphosis diseases.
- Detect fraud in credit card transactions.
Key Course Highlights:
- This comprehensive machine learning course includes over 75 HD video lectures with over 11 hours of video content.
- The course contains 10 practical hands-on python coding projects that students can add to their portfolio of projects.
- No intimidating mathematics, we will cover the theory and intuition in clear, simple and easy way.
- All Jupyter noteboooks (codes) and slides are provided.
- 10+ years of experience in machine learning and deep learning in both academic and industrial settings have been compiled in this course.
Students who enroll in this course will master machine learning classification models and can directly apply these skills to solve real world challenging problems.