The approach presented in this section is based on the use case of classifying a high rate of incoming stream tweets. The task at hand is to extract the embedded sentiments within the tweets about a chosen topic. The sentiment classification quantifies the polarity in each tweet in real time and then aggregate the total sentiments from all tweets to capture the overall sentiments about the chosen topic. To face the challenges posed by the content and behavior of Twitter stream data and perform the real-time analytics efficiently, we use NLP by using a trained classifier. The trained classifier is then plugged into the Twitter stream to determine the polarity of each tweet (positive, negative, or neutral), followed by the aggregation and determination of the overall polarity of all tweets about a certain topic. Let's see how this...
40 Algorithms Every Programmer Should Know
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40 Algorithms Every Programmer Should Know
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Overview of this book
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.
You’ll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, such as searching and sorting, with the help of practical examples. As you advance to a more complex set of algorithms, you'll learn about linear programming, page ranking, and graphs, and even work with machine learning algorithms, understanding the math and logic behind them. Further on, case studies such as weather prediction, tweet clustering, and movie recommendation engines will show you how to apply these algorithms optimally. Finally, you’ll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.
By the end of this book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.
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Current Title:
40 Algorithms Every Programmer Should Know
Table of Contents (19 chapters)
Preface
Section 1: Fundamentals and Core Algorithms
Free Chapter
Overview of Algorithms
Data Structures Used in Algorithms
Sorting and Searching Algorithms
Designing Algorithms
Graph Algorithms
Section 2: Machine Learning Algorithms
Unsupervised Machine Learning Algorithms
Traditional Supervised Learning Algorithms
Neural Network Algorithms
Algorithms for Natural Language Processing
Recommendation Engines
Section 3: Advanced Topics
Data Algorithms
Cryptography
Large-Scale Algorithms
Practical Considerations
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