In this course on Machine Learning I acquired knowledge on how to build systems that learn and adapt using real-world applications. Some of the topics covered include machine learning, python data analysis, deep learning frameworks, natural language processing models and recurrent models.
- Introduction to python and ML
- Linear Models
- SVM & Decision Trees
- Machine Learning as a Service
- Ensembles
- Random Forest
- Feature Engineering
- Unbalanced Learning
- Natural Language Processing
- Sentiment Analysis