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
- All
- Machine Learning (12)
- Networking (3)
- Math and Logic (3)
- Deep Learning (3)
- Sorting (1)
- Security (1)
- Concurrency (1)
- Algorithms (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 Concurrency
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 Machine Learning
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 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 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 Machine Learning
Learn about the k-armed bandit setting and its relation to reinforcement learning.