Machine learning

Classical algorithms, model evaluation, feature work and the maths behind them.

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Probability in Machine Learning with Python8 min
Probability theory forms the backbone of many machine learning algorithms. It provides a framework for dealing with uncertainty and making predictions based...
Probability Theory for Machine Learning with Python9 min
Probability theory forms the backbone of many machine learning algorithms, enabling us to make predictions and decisions in uncertain environments. This...
Quantization Techniques for Large Machine Learning Models10 min
Quantization is a crucial technique in optimizing large machine learning models, particularly neural networks. It involves reducing the precision of the...
Revamping E-commerce with Machine Learning in Python5 min
Introduction to Machine Learning for E-commerce
Role of Cost Functions in Machine Learning11 min
A cost function, also known as loss function, measures the difference between predicted and actual values in machine learning models. It quantifies the error...
Second-Order Equations in Machine Learning Algorithms Using Python7 min
Introduction to Second-Order Equations in Machine Learning and AI
Self-Supervised Learning with SimCLR in TensorFlow11 min
SimCLR (Simple Framework for Contrastive Learning of Visual Representations) is a self-supervised learning technique for computer vision tasks. It allows...
SelfGoal in Machine Learning with Python13 min
SelfGoal is a novel approach in machine learning that focuses on self-supervised learning and goal-oriented behavior. It aims to create models that can...
Sequence Data in Machine Learning with Python9 min
Sequence data is a type of structured data where elements are ordered in a specific manner. In machine learning, working with sequence data is crucial for...
Solving the Traveling Salesman Problem with Machine Learning in Python7 min
Introduction to the Traveling Salesman Problem
Spectral Clustering with Nonlinear Kernel Embedding and FDA8 min
Spectral clustering is a powerful technique for unsupervised learning that leverages the eigenvalues of similarity matrices to perform dimensionality...
Statistical Methods for Machine Learning in Python10 min
Statistical methods form the backbone of many machine learning algorithms. They provide the mathematical foundation for understanding data patterns, making...
Statistical Tests and Machine Learning for Process Engineering7 min
Statistical tests and machine learning techniques are essential tools for process engineers. This presentation covers fundamental statistical tests and...
Strategies for Working with Small Datasets in Machine Learning10 min
Small datasets are a common challenge in machine learning. Despite their limitations, there are various strategies to effectively work with them. This...
Surreal Numbers and Cohomology Theory in Machine Learning10 min
Surreal numbers and cohomology theory are advanced mathematical concepts that have found applications in machine learning. This presentation explores their...
The Role of Calculus in Machine Learning7 min
While it's true that calculus is a valuable tool in machine learning, it's not entirely accurate to say that starting ML without understanding calculus is...
Trust Region Method for Optimization in Machine Learning11 min
The Trust Region Method is an optimization algorithm used in machine learning and artificial intelligence to find the minimum of a function. It's...
Understanding APIs The Bridge Between Client and Server14 min
Modern APIs frequently require secure authentication, proper request formatting, and efficient response handling. A robust API client class encapsulates...
Understanding Machine Learning Distances10 min
The Euclidean distance represents the straight-line distance between two points in n-dimensional space. It's calculated as the square root of the sum of...
Understanding Mutual Information in Machine Learning with Python9 min
Mutual Information (MI) is a measure of the mutual dependence between two variables. It quantifies the amount of information obtained about one random...
When to Use and Avoid MAPE Error10 min
Mean Absolute Percentage Error (MAPE) is a fundamental metric in time series forecasting and regression analysis. This implementation demonstrates the basic...
Why Calculus is Essential for Machine Learning9 min
Calculus is not just a mathematical concept; it's a fundamental tool that empowers machine learning practitioners to understand and optimize their models....
6 Types of Clustering Algorithms Beyond K-Means13 min
K-means clustering revolutionized data partitioning by iteratively assigning data points to their nearest centroids and updating centroid positions. This...
Accelerating KMeans Clustering with Approximate Nearest Neighbors10 min
The K-means clustering algorithm partitions n observations into k clusters by iteratively assigning points to their nearest centroid and updating centroids...
Advanced Clustering Techniques in Machine Learning in Python6 min
Introduction to Advanced Clustering Techniques
Advantages of Random Forest Algorithm in Python12 min
Random Forest is a powerful machine learning algorithm that leverages the strength of multiple decision trees to make predictions. It combines the output of...
Advantages of Support Vector Machines for Robust Classification10 min
Support Vector Machines (SVM) establish optimal decision boundaries by maximizing the margin between classes, creating a robust separator that enhances...
Building a Naive Bayes Classifier from Scratch in Python7 min
Naive Bayes is a probabilistic machine learning algorithm based on Bayes' theorem. It's widely used for classification tasks, particularly in text...
Building a Support Vector Machine (SVM) Algorithm from Scratch in Python11 min
Support Vector Machines (SVM) are powerful supervised learning models used for classification and regression tasks. They work by finding the optimal...
Building DBSCAN Clustering Algorithm from Scratch in Python8 min
DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a popular clustering algorithm used in data mining and machine learning. It groups...