Learn about novelty, concept and data drifts.
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)
Learn about outliers in datasets and why they are important.
Explore overfitting and underfitting in machine learning.
Explore the differences between packets and frames from the OSI model.
Learn the difference between a spinlock and a semaphore.
Understand the IPv4 datagram in detail.
In this tutorial, we’ll learn about different algorithms to generate all k element subsets of a set containing n elements.
Explore the the k-NN algorithm in detail.
Explore two algorithms to find an optimal policy for an Markov Decision Process.
Learn about Fermat’s little theorem and Fermat primality test.
Compare two fundamental sorting algorithms: insertion sort and bubble sort.
Learn about generative and discriminative machine learning algorithms.
Learn about the SVM algorithm and how feature scaling affects its classification success.
Explore two well-known feature scaling methods: normalization and standardization.
Learn about the Naive Bayes classifier and explore ways to improve its classification performance.
Learn how we can utilize the gradient descent algorithm to calculate the optimal parameters of logistic regression.
Have a look at why and how to split a dataset into training and test sets.
Learn about the k-armed bandit setting and its relation to reinforcement learning.