Understand the fundamental building blocks of Machine Learning with Python such as Numpy, Pandas, Data Visualization (Matplotlib, Seaborn and other required libraries) and Scikit- Learn. You will also learn about other latest tools that are used by data scientists today.
– Practice together with Google’s latest Machine Learning Framework in production today – Tensorflow 2.1.
– Here you will learn about three types of machine learning techniques , namely Supervised, Semi-Supervised and Unsupervised Learning.
– Then you will learn anout K-Means clustering, Regression (logistics and linear), Random Forests, Decision Trees etc.
– Here we learn the basic building blocks of AI – which is mainly Machine and Deep Learning.
– Then you will learn about two most popular forms of Machine Learning – namely Computer Vision and NLP (Natural Language Processing).
– Successful ML architectures such as Tensorflow and Pytorch will be discussed as well as best practices for training Machine Learning Models.
– You will start with basic hands-on training to understand how Machine Learning works in real-world.
– You will cover topics in Computer Vision and NLP to both classify and generate text.
– You will learn about best practices for deploying machine learning models in production.
– Take away: Live demo of a fully functioning Machine Learning Cancer Classifier App. You can build one yourself!
If you can not participate this course, you can send someone else instead of you. If cancellation is done less than 14 days before the course start, we will charge 50% of the price. In case of no show without any cancellation, we will charge the whole price. Cancellation fee will also be charged in case of illness.