This is the code repository for 40 Algorithms Every Programmer Should Know , published by Packt.
Hone your problem-solving skills by learning different algorithms and their implementation in Python
Algorithms have always played an important role in both the science and practice of computing. Beyond traditional computing, the ability to use algorithms to solve real-world problems is an important skill that any developer or programmer must have. This book will help you not only to develop the skills to select and use an algorithm to solve real-world problems but also to understand how it works.
This book covers the following exciting features:
- Explore existing data structures and algorithms found in Python libraries
- Implement graph algorithms for fraud detection using network analysis
- Work with machine learning algorithms to cluster similar tweets and process Twitter data in real time
- Predict the weather using supervised learning algorithms
- Use neural networks for object detection
- Create a recommendation engine that suggests relevant movies to subscribers
- Implement foolproof security using symmetric and asymmetric encryption on Google Cloud Platform (GCP)
If you feel this book is for you, get your copy today!
- Page 64: The line "The total number of passes is shown in the following diagram:" and the following diagram are included by mistake on this page and must be ignored/omitted.
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
define swap(x, y)
buffer = x
x = y
y = buffer
Following is what you need for this book: This book is for the serious programmer! Whether you are an experienced programmer looking to gain a deeper understanding of the math behind the algorithms or have limited programming or data science knowledge and want to learn more about how you can take advantage of these battle-tested algorithms to improve the way you design and write code, you’ll find this book useful. Experience with Python programming is a must, although knowledge of data science is helpful but not necessary.
With the following software and hardware list you can run all code files present in the book (Chapter 1-14).
| Chapter | Software required | OS required |
|---|---|---|
| 1-14 | Python version 3.7.2 or later | Windows/Linux/Mac |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
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Modern Computer Architecture and Organization [Packt] [Amazon]
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Mastering Machine Learning Algorithms - Second Edition [Packt] [Amazon]
Imran Ahmad is a certified Google Instructor and has been teaching for Google and Learning Tree for the last many years. The topics Imran teaches include Python, Machine Learning, Algorithms, Big Data and Deep Learning. In his PhD, he proposed a new linear programming based algorithm called ATSRA , which can be used to optimally assign resources in a cloud computing environment. For the last 4 years, Imran is working in a high-profile machine learning project at the advanced analytics lab of the Canadian Federal Government. The project is to develop machine learning algorithms that can automate the process of immigration. Imran is currently working on developing algorithms to use GPUs optimally to train complex machine learning models.
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