Course Description
This comprehensive Data Science and Machine Learning course begins with a thorough introduction to Python, including a crash course and exercises with solutions provided. Moving on to Data Science, topics cover data parsing with Scrapy, data visualization using Python libraries, and various data preprocessing techniques, culminating in a collaborative project. Subsequently, learners delve into classical and advanced machine learning algorithms, implemented both from scratch and utilizing Python’s built-in libraries, followed by mini-projects for each algorithm. The course concludes with an exploration of Deep Learning, including artificial neural network structure and TensorFlow implementation, alongside a deep learning-based project and discussions on hyperparameter tuning techniques to enhance model performance.
What You’ll Learn?
- Data Science:(Online Data Parsing, Data visualization, Data Preprocessing, Preparing data for machine learning)
- Machine Learning:(Supervised Machine Learning, Unsupervised Machine Learning, Implementation of algorithms form scratch, Built-in algorithms usages.)
- Deep Learning:(Tensorflow, Hyperparameter tunings)
- Working with some data sets which are benchmarks in industry like : Titanic, Seeds, Rock and Mine
Lessons:
