Matrices & Determinants - IIT JEE Mathematics
Comprehensive study of matrices and determinants for IIT JEE Mathematics, covering key concepts, problem-solving techniques, and exam preparation through lectures, quizzes, and mock tests.
NDA Exam Preparation Videos - Maths
Comprehensive NDA math preparation covering key topics with expert instruction, visualizations, and practice materials for exam success.
NDA, Air Force & Navy Master Classes Maths by Vikas Tiwari
Comprehensive mathematics preparation for NDA, Air Force Group X, and Navy exams, covering key topics like trigonometry, probability, calculus, and more with expert instructor Vikas Tiwari.
UPSC NDA Maths by Neeraj Baisla
Comprehensive mathematics preparation for UPSC NDA, Air Force, and Navy exams, covering probability, statistics, vectors, trigonometry, geometry, and calculus through lectures and problem-solving sessions.
Maharashtra State Board Class 10 Maths Financial Planning
Comprehensive guide to financial planning, GST, shares, and dividends for Class 10 students, featuring chapter introductions, exercise solutions, and exam-focused content.
Quant Shortcuts for CAT-MBA Exams
Master quantitative shortcuts for MBA entrance exams, covering probability, number theory, algebra, geometry, and more. Learn time-saving techniques to solve complex problems quickly and efficiently.
Basics of Quants Entrance Prep
Comprehensive quantitative aptitude preparation covering key topics for MBA entrance exams. Includes theory, practice sessions, and problem-solving techniques to build a strong foundation in mathematics.
NumPy Data Science Essential Training With Python 3
Master NumPy for data science: arrays, indexing, computation, visualization, and statistical analysis. Hands-on practice with Python 3 and Jupyter Notebook for real-world applications.
Machine Learning and Deep Learning Maths - Matrix and Vector Operations
Explore essential matrix and vector operations for machine learning and deep learning using Python, covering creation, manipulation, and mathematical computations.
IT Data Structures Class - University of South Florida Fall 2016
Comprehensive exploration of data structures, covering arrays, STL containers, C++ classes, and Big O notation. Includes practical coding examples and best practices.
C++
Master C++ essentials: arrays, loops, STL containers, file I/O, classes, and Big O notation. Hands-on practice with CLion IDE and modern C++ features.
C++ Programming
Learn essential C++ programming concepts and apply them to game development using SFML. Master variables, vectors, loops, sprites, user interactions, and game maps for diverse applications.
Learn TensorFlow and Deep Learning Fundamentals with Python - Code-First Introduction Part 1-2
Comprehensive introduction to TensorFlow and deep learning fundamentals, covering tensor operations, neural network regression, and classification. Hands-on coding examples and practical insights for building and improving models.
The State of Julia in 2021 - JuliaCon Keynote
Comprehensive overview of Julia's progress in 2021, covering threading, compiler improvements, linear algebra advancements, package updates, and future development plans.
Interplay of Linear Algebra, Machine Learning, and HPC - JuliaCon 2021 Keynote
Explore the interplay of linear algebra, machine learning, and HPC with Dr. Li. Learn about fast solvers, low-rank compression, and how ML can optimize linear algebra computations for big data problems.
Principal Component Analysis - Lecture 8
Explore Principal Component Analysis: from matrix rank to SVD. Learn to measure data cloud size, understand correlated data, and navigate high-dimensional spaces using statistical techniques.
Transformations - Composability and Linearity in Computational Thinking - Lecture 4
Explore composability and linearity in transformations, focusing on image processing applications and advanced Julia programming techniques for vector-valued functions and linear/nonlinear transformations.
Transformations and Automatic Differentiation in Computational Thinking - Lecture 3
Explore transformations and automatic differentiation in Julia, covering linear and non-linear transformations, function types, and applications in machine learning, with practical examples and visualizations.
Transforming Images and Image Processing Techniques - Lecture 2
Explore image transformation techniques using Julia, including downsampling, linear combinations, convolutions, and filters. Learn about complexity, GPUs, and data structures in computational thinking.
Matrix Calculus for Linear Algebra - MIT 18.06 Spring 2020
Comprehensive exploration of matrix calculus, covering gradients, Jacobians, and advanced concepts. Ideal for those seeking a deep understanding of mathematical foundations in linear algebra.
Understanding Structure in Data - Week 3
Explore data structure analysis using Julia, covering matrix rank, data visualization, PCA, and building a simple recommendation engine. Gain practical insights into advanced data science concepts.