ML & AI
Master Machine Learning & Artificial Intelligence: Unlock the Power of Data and Automation
Step into the world of Machine Learning (ML) and Artificial Intelligence (AI) with our in-depth courses designed for all skill levels. Learn the key concepts, algorithms, and techniques behind ML and AI, and how they’re transforming industries such as healthcare, finance, and technology. From supervised and unsupervised learning to deep learning and neural networks, our courses provide hands-on experience with the latest tools and frameworks. Whether you’re a beginner or an advanced professional, develop the expertise to build intelligent systems and drive innovation with ML & AI.
Large Language Models
Course on Large Language Models NOTE: You’re only meant to change code marked with “# TODO:” Table of Contents Setting Up API Key Configuration Connecting to OpenAI API Exploring the API Creating Chat Completions Understanding Completion Parameters Prompt Engineering Crafting Effective Prompts Strategies and Best Practices Advanced Techniques Utilizing Embeddings Function Calling in LLMs Extras…
Everything You Need to Know About SciPy
What is SciPy? SciPy is an interactive Python session used as a data-processing library that is made to compete with its rivalries such as MATLAB, Octave, R-Lab, etc. It has many user-friendly, efficient, and easy-to-use functions that help to solve problems like numerical integration, interpolation, optimization, linear algebra, and statistics. The benefit of using the…
Numerical Analysis A Step-by-Step Guide to Solving Polynomial Equations
Numerical Analysis is the study of algorithms for solving mathematical problems involving continuous variables. It differs from discrete mathematics and focuses on deriving and analyzing methods to obtain numerical solutions.
Linear Algebra Topics – Decoded with Examples and Calculations Explained Step by Step
A linear equation is an equation involving a linear combination of variables.
Probability Distributions: Formulas, CDFs, PMFs, and Examples
In probability theory, a probability distribution is a mathematical function that provides the probabilities of occurrence of different possible outcomes in an experiment. These distributions are either discrete or continuous, depending on whether the outcomes are countable or measurable over a range of values.
The Mathematics Behind Neural Networks Detailed Derivation of Key Formulas
Neural networks are the backbone of modern artificial intelligence (AI), powering applications like image recognition, natural language processing, and autonomous vehicles,
Let’s break down AI, Machine Learning (ML), and Neural Networks in a structured way
Let’s break down AI, Machine Learning (ML), and Neural Networks in a structured way, covering key concepts, types of ML, and model architectures like Transformers, and their applications.
Complete Breakdown of Machine Learning (ML)
Machine Learning
is a vast and intricate field that requires an understanding of key concepts from mathematics, statistics, programming, and data science. Let’s go through everything step-by-step, from the fundamental maths to the essential skills required to build ML models.
Transformers: Revolutionizing Natural Language Processing (NLP)
In the ever-evolving field of Natural Language Processing (NLP), the introduction of transformers has marked a major turning point.