Learn about novelty, concept and data drifts.

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# Baeldung Author

## A. Aylin Tokuç

I’m a Computer Scientist/Researcher, specialized in machine learning and data science. I have 15 years of professional work experience. Currently I develop freelance projects to help businesses automate and optimize their decision-making processes. I'm also pursuing a Ph.D. degree.

## Here's what I've written (so far):

## Baeldung on Computer Science on Java

- Machine Learning (11)
- Deep Learning (4)
- Networking (3)
- Math and Logic (3)
- Artificial Intelligence (2)
- Algorithms (2)
- Sorting (1)
- Security (1)
- OS (1)
- Core Concepts (1)

### Outlier Detection and Handling

Filed under Deep Learning, Machine Learning

Learn about outliers in datasets and why they are important.

### Underfitting and Overfitting in Machine Learning

Filed under Machine Learning

Explore overfitting and underfitting in machine learning.

### OSI Model: Packets vs. Frames

Filed under Networking

Explore the differences between packets and frames from the OSI model.

### Spinlock vs. Semaphore

Filed under OS

Learn the difference between a spinlock and a semaphore.

### IPv4 Datagram

Filed under Networking

Understand the IPv4 datagram in detail.

### Algorithms to Generate k-Combinations

Filed under Networking, Security

In this tutorial, we’ll learn about different algorithms to generate all *k* element subsets of a set containing *n* elements.

### k-Nearest Neighbors and High Dimensional Data

Filed under Deep Learning, Machine Learning

Explore the the k-NN algorithm in detail.

### Value Iteration vs. Policy Iteration in Reinforcement Learning

Filed under Deep Learning, Machine Learning

Explore two algorithms to find an optimal policy for an Markov Decision Process.

### Fermat Primality Test

Filed under Math and Logic

Learn about Fermat’s little theorem and Fermat primality test.

### Insertion Sort vs. Bubble Sort Algorithms

Filed under Algorithms, Sorting

Compare two fundamental sorting algorithms: insertion sort and bubble sort.

### Generative vs. Discriminative Algorithms

Filed under Algorithms, Core Concepts

Learn about generative and discriminative machine learning algorithms.

### Why Feature Scaling in SVM?

Filed under Machine Learning

Learn about the SVM algorithm and how feature scaling affects its classification success.

### Normalization vs Standardization in Linear Regression

Filed under Machine Learning

Explore two well-known feature scaling methods: normalization and standardization.

### How to Improve Naive Bayes Classification Performance?

Filed under Artificial Intelligence, Machine Learning, Math and Logic

Learn about the Naive Bayes classifier and explore ways to improve its classification performance.

### Gradient Descent Equation in Logistic Regression

Filed under Machine Learning, Math and Logic

Learn how we can utilize the gradient descent algorithm to calculate the optimal parameters of logistic regression.

### Splitting a Dataset into Train and Test Sets

Filed under Artificial Intelligence, Machine Learning

Have a look at why and how to split a dataset into training and test sets.

### Solving the K-Armed Bandit Problem

Filed under Deep Learning, Machine Learning

Learn about the k-armed bandit setting and its relation to reinforcement learning.