Sukhrobjon Golibboev (Sukhrobjon)

Sukhrobjon

Geek Repo

Company:@microsoft

Location:Redmond

Github PK Tool:Github PK Tool

Sukhrobjon Golibboev's repositories

deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

CS-1.3-Core-Data-Structures-SG

This course explores the foundations of computer science including discrete mathematics, abstract data types, data structures, and algorithm analysis and design. Students will compare and contrast iterative and recursive algorithms to analyze design and performance tradeoffs. Students will apply and test data structures like lists, stacks, queues, sets, maps, and trees in real-world problems such as phone call routing. Students will also write technical blog articles about these topics in order to deepen their understanding and gain valuable online presence as knowledgeable and proficient software engineers.

Language:PythonLicense:MITStargazers:2Issues:2Issues:3

self-driving-cars-graph

CS-2.2 Graph project proposal

Language:PythonLicense:MITStargazers:2Issues:2Issues:2

flask-blog

Flask blog personal project to learn how flask and python is used for backend purpose

Language:HTMLStargazers:1Issues:2Issues:0

CS-1.2-How-Data-Structures-Work

CS 1.2: How Data Structures Work

Language:PythonStargazers:0Issues:2Issues:0

autocomplete-searchbar

USF collaboration project front end

Language:CSSLicense:MITStargazers:0Issues:2Issues:0

BEW-1.2-Authentication-and-Associations

🔐 Build on knowledge of Resourceful and RESTful patterns and dive deep into the Node and Express ecosystem.

Language:JavaScriptStargazers:0Issues:2Issues:0

BEW-2.1-Advanced-Web-Patterns

👩‍💻Be able to build anything by learning the commonest advanced patterns for web development like search, file uploading, and sending emails and texts. We will also look at advanced JS topics like async/await and projects like TypeScript.

Stargazers:0Issues:2Issues:0

call_routing_project

CS-1.3 Final project

Language:PythonStargazers:0Issues:2Issues:0

Core-Git-Branching

Starter project for advanced Git branching lesson

Stargazers:0Issues:2Issues:0

CS-1.3-Core-Data-Structures

CS 1.3: Core Data Structures & Algorithms

Language:PythonLicense:MITStargazers:0Issues:2Issues:0

CS-2.2-Advanced-Recursion-and-Graphs

CS 2.2: Advanced Recursion and Graphs – Course Syllabus and Lessons

Language:HTMLLicense:MITStargazers:0Issues:0Issues:0

CS-2.2-Challenges

This course covers graph theory, data structures, algorithms, and analysis. Key concepts include recursion, greedy algorithms, memoization and dynamic programming. Students will build an original project whose underlying structure requires the use of graph structures and algorithms to solve real-world problems such as airplane routing, social networking, and board games.

Language:PythonLicense:MITStargazers:0Issues:1Issues:5
Language:PythonLicense:MITStargazers:0Issues:1Issues:0

DS-1.1

Learn the foundational skills of data science, including data collection, cleaning, analysis, and visualization with modern tools and libraries. Master the science and art of data exploration and visualization to tell stories with discoveries and persuade decision makers with data-driven insights. Collect a dataset, explore, analyze, and visualize it to discover trends, then present original insights. Gain a strong grounding in statistical concepts including measures of center and spread, distributions, sampling, and the central limit theorem. Utilize statistical techniques to calculate z-scores and confidence intervals, perform hypothesis tests, and identify outliers.

Language:Jupyter NotebookStargazers:0Issues:2Issues:0

DS-1.1-Data-Analysis

DS 1.1: Data Analysis & Visualization

Language:Jupyter NotebookStargazers:0Issues:2Issues:0

DS-2.1-ML-Challenges

Students will learn the foundational concepts and techniques of machine learning and how to apply those techniques to data science. Principles of data science and machine learning will be examined and applied to problem solving. Students will master data science processes and its applications, including how to wrangle and use data to train classification or prediction models. To demonstrate mastery, students will apply these techniques to develop and train models on data sets using industry-standard modern software libraries and tools. Students will develop “sharp” data science questions, select a data set and apply a variety of methods to explore those questions and find relevant answers.

Language:Jupyter NotebookStargazers:0Issues:2Issues:0
Language:PythonLicense:MITStargazers:0Issues:1Issues:0
License:MITStargazers:0Issues:2Issues:0
Language:JavaScriptStargazers:0Issues:2Issues:0

passport-auth

BEW-1.2 In class exercise

Language:JavaScriptStargazers:0Issues:2Issues:0

Rotten-Potatoes

BEW-1.1-MakeSchool

Language:JavaScriptStargazers:0Issues:2Issues:0

single-source

The place I upload my notes learnings from school and academic wise in general.

Stargazers:0Issues:2Issues:0

summer-2019-internships

A document to help undergraduates keep track of software engineering internship opportunities.

Stargazers:0Issues:2Issues:0

take-home-project-SPD

SPD-1.02 project

License:MITStargazers:0Issues:2Issues:0

tdd-bdd-challenge

🧪 [BEW 1.2] Day 9 TDD/BDD challenges in Mocha and Chai

Language:JavaScriptLicense:MITStargazers:0Issues:2Issues:0

three.js

JavaScript 3D library.

Language:JavaScriptLicense:MITStargazers:0Issues:0Issues:0

visualize-time-column

visualize-time-column of dataframe using flask

Language:PythonLicense:MITStargazers:0Issues:2Issues:0

We-sell-shoes

FEW-1.1- MakeSchool

Language:CSSStargazers:0Issues:2Issues:1