From Binomial Distributions to Normal Distributions — While I was studying Statistical Physics at the university, I was fascinated by the ability of statistics to simplify and explain the chaotic processes in a smart approach. When I started to study data science, I found too much resemblance between Statistical Physics and Data Statistics. This is the topic…

Dice and Jaccard’s explained… — We are working on a deep learning model that predicts masks for brain tumors or skin lesions. What is making a mask? We classify pixels of an image as 1 or 0. If there is a mask in a pixel we state 1, if there is not a mask we…

Comparison of dictionaries and lists — Imagine that you are organizing a data science conference. You are making a list of attendees. Later you want to look up a name in this attendee list. How much time does it take to find a name if you store the data as a list, and as a dictionary…

Reference Counting and Generational Garbage Collection — You are at the right place if you have these questions while learning Python: How is memory managed in Python? What is garbage collection? Which algorithms are used for memory management? What is a cyclical reference? How are Python objects stored in memory? Let’s see if I can answer these…

Comparing Distributions — Kolmogorov-Smirnov(K-S) test In statistics, Kolmogorov-Smirnov(K-S) test is a non-parametric test of the equality of the continuous, one-dimensional (univariate) probability distributions. K-S test compares the two cumulative distributions and returns the maximum difference between them. One-sample K-S test or goodness of fit test was developed by Andrey Nikolayevich Kolmogorov in 1933. …

K-Fold Cross Validation Explained… — In last week’s article, I wrote about train-test splits. However, there is a problem with separating the data into only two splits. Since we create random samples of data, the test and train performances can be very different depending on our train-test split. We must validate our model more than…

Train-Test Split Explained… — This article is a detailed explanation for the interview question below. Why is it important to create a separate evaluation split of a dataset when performing model/algorithm tuning in supervised learning? Predictive Models We create predictive models to be able to guess the outcome for the unseen data. In order to measure…

Bias-Variance Dilemma — What is bias-variance tradeoff? This question is frequently asked in machine learning interviews. Although it is an entry-level question, you can demonstrate your understanding of machine learning by explaining the answer beautifully. …

How Similar Animals And Computers Learn? — Reinforcement Learning Reinforcement learning(RL) is a type of deep learning that has been receiving a lot of attention in the past few years. It is useful for the situations we want to train AI for certain skills we don’t fully understand. RL has an agent that takes actions in an uncertain environment…