Leonard Eddison

Python Machine Learning Leonard Eddison

Python Machine Learning
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This book contains:
Python Machine Learning: A Deep Dive Into Python Machine Learning and Deep Learning, Using Tensor Flow And Keras: From Beginner To Advance
Python: A Complete Step By Step Beginners Guide To Programming With Python
No previous experience with Keras, TensorFlow, or machine learning is required.
What exactly is machine learning and why is it so valuable in the online business world? Simply put, it is a method of data analysis that uses algorithms that learn from data and produce specific results without being specifically programmed to do so. These algorithms can analyze data, calculate how frequently certain parts of it are used and generate responses based on this calculations in order to automatically interact with users.
Throughout the recent years, artificial intelligence and machine learning have made some enormous, significant strides in terms of universal, global applicability. The ability to now be able to apply such algorithms via traditional and new dynamic programming languages allows us to interpret and understand these approaches much more eloquently.
The main topics:
-Why Machine Learning
-Machine Learning And Artificial Intelligence
-Some of the branches of Artificial Intelligence
-Keras CNN Model for Deep Learning Predictions on AMZN
Applying Logistic Regression to U. S. Equity Markets for Predictive Trading
Python Machine Learning Applied To Financial Markets
-What Python is and how to get started with it
-What input and output mean in Python
-The way that Python evolved throughout time After reading this book you will be able to implement machine learning and deep learning using Python
While machine and deep learning algorithms have become a common measure for significant model performance across multiple industries, the primary focus of this book will be to better understand how such algorithms are being applied specifically via financial markets through the usage of the Python programming language.