Description
Size: 19.2 GB
What you’ll learn
- ✓Become a Data Scientist and get hired
- ✓Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0
- ✓Present Data Science projects to management and stakeholders
- ✓Real life case studies and projects to understand how things are done in the real world
- ✓Implement Machine Learning algorithms
- ✓How to improve your Machine Learning Models
- ✓Build a portfolio of work to have on your resume
- ✓Supervised and Unsupervised Learning
- ✓Explore large datasets using data visualization tools like Matplotlib and Seaborn
- ✓Learn NumPy and how it is used in Machine Learning
- ✓Learn to use the popular library Scikit-learn in your projects
- ✓Master Machine Learning and use it on the job
- ✓Use modern tools that big tech companies like Google, Apple, Amazon and Facebook use
- ✓Learn which Machine Learning model to choose for each type of problem
- ✓Learn best practices when it comes to Data Science Workflow
- ✓Learn how to program in Python using the latest Python 3
- ✓Learn to pre process data, clean data, and analyze large data.
- ✓Developer Environment setup for Data Science and Machine Learning
- ✓Machine Learning on Time Series data
- ✓Explore large datasets and wrangle data using Pandas
- ✓A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided
- ✓Learn about Data Engineering and how tools like Hadoop, Spark and Kafka are used in the industry
- ✓Learn how to apply Transfer Learning
- ✓Learn to perform Classification and Regression modelling
