Machine learning
Classical algorithms, model evaluation, feature work and the maths behind them.
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- Comparing Gini Impurity and Entropy in Decision Trees14 min
The Gini impurity metric quantifies the probability of incorrect classification when randomly choosing an element from a dataset based on the class...
- Decoding the Decoder Understanding its Role in Machine Learning Models8 min
The Decoder is a crucial component in many machine learning models, particularly in sequence-to-sequence architectures like transformers. It takes encoded...
- Demystifying Machine Learning When Theory Meets Practice13 min
Linear algebra's foundation in ML starts with vectors. Vectors represent features, parameters, or data points in n-dimensional space, forming the basic...
- Emotional Rollercoaster of Training Machine Learning Models8 min
Early stopping is a regularization technique that prevents overfitting by monitoring the model's performance on a validation set during training. When the...
- Explaining Forward Elimination in Machine Learning with Python12 min
Forward Elimination is a crucial step in solving systems of linear equations using Gaussian elimination. It's a systematic process of transforming a matrix...
- Explaining the Decoder in Machine Learning Models with Python13 min
The decoder is a crucial component in many machine learning models, particularly in sequence-to-sequence architectures. It takes the encoded representation...
- Exploring Loss Landscapes in Machine Learning11 min
The loss landscape represents the error surface over which optimization occurs during neural network training. It's a high-dimensional space where each...
- How to Fail at Machine Learning10 min
Data leakage occurs when information from outside the training dataset influences the model development process, leading to overoptimistic performance...
- Importance of Listing Assumptions in Machine Learning with Python12 min
In machine learning, assumptions play a crucial role in model development and performance. They shape our understanding of the problem, guide our choice of...
- Importance of Physical Intuition in Machine Learning9 min
Physical interpretations and intuitions of equations are indeed crucial in Machine Learning and Data Science. They help us understand complex concepts...
- Introduction to Machine Learning with Python10 min
Machine Learning (ML) is a subset of Artificial Intelligence that focuses on developing algorithms and statistical models that enable computer systems to...
- Introduction to Supervised and Unsupervised Machine Learning18 min
Supervised learning classification involves training models to categorize data into predefined classes using labeled examples. This fundamental approach...
- Linear Algebra Foundations for Machine Learning12 min
Linear algebra operations form the backbone of machine learning algorithms. Understanding vector and matrix manipulations is crucial as they represent...
- Linear Algebra Fundamentals for Machine Learning8 min
Linear algebra operations form the backbone of machine learning algorithms. Understanding vector operations is crucial for implementing efficient ML models...
- Machine Learning Algorithms Handwritten Notes16 min
Machine learning is a subset of artificial intelligence that enables systems to learn and improve from experience without explicit programming. It uses...
- Machine Learning Lifecycle in Python4 min
The foundation of any machine learning project begins with gathering relevant data. High-quality data collection is crucial for model performance. Data can...
- Machine Learning Lifecycle with Python6 min
The machine learning lifecycle encompasses the entire process of developing, deploying, and maintaining machine learning models. It includes data collection...
- Machine Learning Math & Algorithms Demystified10 min
Machine Learning is not magic, but a powerful combination of mathematics and algorithms. It's a subset of artificial intelligence that focuses on creating...
- Machine Learning Python Cheat Sheet10 min
Machine Learning is a branch of artificial intelligence that focuses on developing algorithms and models that enable computers to learn from and make...
- Machine Learning System Design11 min
Machine learning problems typically involve tasks where a system learns patterns from data to make predictions or decisions. These problems can range from...
- Machine Learning Techniques in Python12 min
Machine learning encompasses various techniques for analyzing and interpreting data. This presentation will cover four fundamental areas: Regression...
- Machine Learning Workflow 10 Key Processes10 min
Data collection is the foundation of any machine learning project. It involves gathering relevant information from various sources such as databases, APIs...
- Major Forms of Machine Learning8 min
Machine Learning (ML) is a rapidly evolving field with various approaches to teaching computers how to learn from data. This presentation covers eight major...
- Mastering Machine Learning Algorithms23 min
Linear regression forms the foundation of predictive modeling by establishing relationships between variables. This implementation demonstrates how to build...
- Mastering Machine Learning Foundations10 min
Linear algebra forms the mathematical backbone of machine learning algorithms. Understanding vector spaces, transformations, and matrix operations is crucial...
- Mastering Machine Learning The Importance of Mathematical Foundations11 min
Machine learning is not just about using tools like scikit-learn. A solid understanding of the underlying mathematics is crucial for long-term success in the...
- Mastering Statistics for Data Science and Machine Learning5 min
Statistics forms the foundation of data science and machine learning. It provides the tools to analyze, interpret, and draw meaningful insights from data....
- Math Foundations for Machine Learning11 min
Machine learning and statistics are closely related fields that deal with data analysis and prediction. While statistics focuses on inferring population...
- Mathematical Foundations for Machine Learning11 min
Mathematical Notation in Linear Algebra and Machine Learning
- ML Algorithms Using Python11 min
Linear Regression is a fundamental algorithm in machine learning used for predicting continuous numerical values based on input features. It models the...