Search Results for "python math"

Perfect Roadmap To Learn Data Science In 2025 is an extended, updated learning pathway curated for the modern data-science landscape — blending classical data-analysis, statistics, machine learning, deep learning, computer vision, NLP, as well as current deployment and MLOps practices to prepare learners for data-science careers in 2025. The roadmap is organized to guide learners systematically: starting with Python fundamentals and math/statistics, then progressing through classical machine-learning, deep-learning, data preprocessing, feature engineering, and onto domain-specific applications like computer vision or NLP, ending with deployment, real-world project construction, and best practices for production readiness. What makes it particularly valuable is its holistic nature: rather than focusing only on modeling or theory, it also addresses the broader lifecycle of data-science work, data ingestion, cleaning, EDA, feature engineering, model building, validation, deployment, etc.

LeetCode-Book is a comprehensive study guide for coding interviews that consolidates algorithm patterns, data-structure templates, and worked LeetCode solutions. It organizes problems by topic—arrays, linked lists, stacks/queues, trees/graphs, dynamic programming, greedy, backtracking, and math—so you can study systematically. Explanations are concise but intentional, highlighting why a pattern fits, how to reason about boundary cases, and the time/space trade-offs. Many entries include...

The Grand Complete Data Science Materials is a repository curated by a data-science educator that aggregates a wide range of learning resources — from basic programming and math foundation to advanced topics in machine learning, deep learning, natural language processing, computer vision, and deployment practices — into a structured, centralized collection aimed at learners seeking a comprehensive path to data science mastery. The repository bundles tutorials, lecture notes, project outlines, course materials, and references across topics like Python, statistics, ML algorithms, deep learning, NLP, data preprocessing, model evaluation, and real-world problem solving. ...

ML-For-Beginners is a structured, project-driven curriculum that teaches foundational machine learning concepts with approachable math and lots of code. Organized as a multi-week course, it mixes short lectures with labs in notebooks so learners practice regression, classification, clustering, and recommendation techniques on real datasets. Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs. The...

Latest version 0.9.1 runs on Python3. Date: June 15, 2023 Online/touch-screen version: https://www.asymptopia.com/tuxmathscrabble Encourages kids to construct compound equations and consider multiple abstract possibilities.

This project aims to produce elementary math worksheets & answers automatically. It is meant to be used - by pupils to get as many sheets as they want - by teachers to re-use the produced sheets in their own work. Documentation for users is there: http://mathmaker.readthedocs.io/en/master/user_index.html

This project provides a math worksheet environment for specially enabled children. Designed as a generic math worksheet for specially enabled persons to workout math problems with limited input in system as we do by hand.

Several scripts for a variety of useful math functions.

This project will provide translation of mathematical content, from TeX to MathML and vice-versa, and to graphics formats, as a web service. TeX, running as a daemon, is used for mathematical typography.

FlashE is an VERY simple electronic flash card system written in python. FlashE is very general and is intended to be as well suited to vocabulary training as math or Biology. The quiz files can be edited or shared.