# Machine Learning

## Human detection and Pose Estimation with Deep Learning for Sport Analysis

Pose estimation and tracking human is one the key step in sports analysis. Here is in this work I used openpose for analysis of player in a Bundesliga game HSV Hamburg vs Bayer München. Warning: the video might be disturbing for HSV fans 🙂   Original Video Analyzed Video Original Video Analyzed Video Original Video Analyzed Video Original Video …

## Breadth-first search (BFS) and Depth-first search (DSF) Algorithm with Python and C++

Python Implementation BFS traverse:

DFS traverse:

C++ Implementation

## RANSAC Algorithm parameter explained

In this tutorial I explain the RANSAC algorithm, their corresponding parameters and how to choose the number of samples: N = number of samples e = probability that a point is an outlier s = number of points in a sample p = desired probability that we get a good sample N =log(1-p) /log(1- (1- …

## Examples of Dynamic Programming with C++ and Matlab

In this tutorial, I will give you examples of using dynamic programming for solving the following problems: 1)Minimum number of coins for summing X.

2)The most (least) costly path on a grid (dynamic time warping).

3)Levenshtein edit distance.

4)Seam Carving. I have written a tutorial on that …

## Seam Carving Algorithm for Content-Aware Image Resizing with Matlab Code

Seam carving is an algorithm for resizing images while keeping the most prominent and conspicuous pixels in the image. The important pixels in an image are usually those who are located over horizontal or vertical edges, so to throw away some pixels we first find horizontal and vertical edges and store their magnitude as pixel …

## Hierarchical Clustring in python

Hierarchical Clustering is a method of clustering which build a hierarchy of clusters. It could be Agglomerative or Divisive. Agglomerative: At the first step, every item is a cluster, then clusters based on their distances are merged and form bigger clusters till all data is in one cluster (Bottom Up). The complexity is \( O (n^2log(n) ) \). Divisive: At the beginning, …

## Maximum likelihood estimation explained

In this tutorial, I explain the “Maximum likelihood” and MLE (maximum likelihood estimation) for binomial and Gaussian distribution.

## Naive Bayes Classifier Explained

In this video, I explain the “Naive Bayes Classifier”. The example has been solved with phyton in my other post here

## Naive Bayes Classifier Example with Python Code

In the below example I implemented a “Naive Bayes classifier” in python and in the following I used “sklearn” package to solve it again: and the output is: