The relationship between features and labels in regression problems is seldom perfectly linear. But it may be linear within our usual operating range. Approximating the relationship as linear greatly simplifies the algorithm and is extensively used. But this also introduces some approximations affecting the accuracy of the algorithm. The trade-off between approximations and accuracy should be carefully studied and the right balance suitable for the stakeholders should be chosen.
- Title Page
- Copyright and Credits
- Dedication
- About Packt
- Contributors
- Preface
- Section 1: Fundamentals and Core Algorithms
- 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
- Introducing unsupervised learning
- Understanding clustering algorithms
- Dimensionality reduction
- Association rules mining
- Practical application– clustering similar tweets together
- Anomaly-detection algorithms
- Summary
- Traditional Supervised Learning Algorithms
- Understanding supervised machine learning
- Understanding classification algorithms
- Presenting the classifiers challenge
- Evaluating the classifiers
- Specifying the phases of classifiers
- Decision tree classification algorithm
- Understanding the ensemble methods
- Logistic regression
- The SVM algorithm
- Understanding the naive Bayes algorithm
- For classification algorithms, the winner is...
- Understanding regression algorithms
- Practical example – how to predict the weather
- Summary
- Neural Network Algorithms
- Algorithms for Natural Language Processing
- Recommendation Engines
- Introducing recommendation systems
- Types of recommendation engines
- Understanding the limitations of recommender systems
- Areas of practical applications
- Practical example – creating a recommendation engine
- Summary
- Section 3: Advanced Topics
- Data Algorithms
- Cryptography
- Introduction to Cryptography
- Understanding the Types of Cryptographic Techniques
- Example – Security Concerns When Deploying a Machine Learning Model
- Summary
- Large-Scale Algorithms
- Practical Considerations
- Other Books You May Enjoy
Example
-
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.