Python Machine Learning Machine Learning and Deep Learning with Python, Scikit-Learn and Tensorflow - Samuel Burns
-25% koodilla BOOKS
Toimitus 10-16 arkipäivässä
30 päivän palautusoikeus
You are interested in becoming a machine learning expert but don't know where to start from? Don't worry you don't need a big boring and expensive Textbook. This book is the best guide for you. Get your copy NOW!! Why this guide is the best one for Data Scientist? Here are the reasons:The author has explored everything about machine learning and deep learning right from the basics. A simple language has bee ... Täydellinen kuvaus
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Kuvaus
- A simple language has been used.
- Many examples have been given, both theoretically and programmatically.
- Screenshots showing program outputs have been added.
- To help you understand the basics of machine learning and deep learning.
- Understand the various categories of machine learning algorithms.
- To help you understand how different machine learning algorithms work.
- You will learn how to implement various machine learning algorithms programmatically in Python.
- To help you learn how to use Scikit-Learn and TensorFlow Libraries in Python.
- To help you know how to analyze data programmatically to extract patterns, trends, and relationships between variables.
- Anybody who is a complete beginner to machine learning in Python.
- Anybody who needs to advance their programming skills in Python for machine learning programming and deep learning.
- Professionals in data science.
- Professors, lecturers or tutors who are looking to find better ways to explain machine learning to their students in the simplest and easiest way.
- Students and academicians, especially those focusing on neural networks, machine learning, and deep learning.
- Python 3.X
- Numpy
- Pandas
- Matplotlib
The Author guides you on how to install the rest of the Python libraries that are required for machine learning and deep learning.
What is inside the book:- Getting Started
- Environment Setup
- Using Scikit-Learn
- Linear Regression with Scikit-Learn
- k-Nearest Neighbors Algorithm
- K-Means Clustering
- Support Vector Machines
- Neural Networks with Scikit-learn
- Random Forest Algorithm
- Using TensorFlow
- Recurrent Neural Networks with TensorFlow
- Linear Classifier
Lisätietoja
| Kirjoittaja | Samuel Burns |
|---|---|
| Julkaisija | Independently Published |
| Julkaisuvuosi | 2019 |
| Kannen tyyppi | Pehmeäkantinen |
| EAN | 9781090434166 |