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Hands-On Machine Learning from Scratch
Develop a Deeper Understanding of Machine Learning Models by Implementing Them from Scratch in Python
This book will guide you on your journey to deeper Machine Learning understanding by developing algorithms in Python from scratch! Learn why and when Machine learning is the right tool for the job and how to improve low performing models!
Hello!
Recent developments in the field of Artificial Intelligence made Machine Learning methods usable and efficient in practice. Tools like PyTorch, TensorFlow, Scikit-Learn make it easy to build your first model.
Unfortunately, reading through a Machine Learning/Deep Learning tutorial showing how to use a library will leave you asking - why does it work, when can I use that and how can I improve it? Now what? This book will help you answer those questions!
What is in for you?
- Step-by-step guide on how to approach, visualize and solve data science problems
- Learn why and when Machine Learning is the right tool for the job
- Learn how to process CSV, text, and image data
- Develop Linear Regression, Logistic Regression, Decision Tree, Neural Network, and other models. Use your models to solve real-world problems.
- Find how to improve low performing models
- Learn how to use Python libraries like NumPy, Pandas, Seaborn and more
- Complete source code (notebooks) that works and runs in the cloud
Welcome to the amazing world of Machine Learning!