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data-science-machine-learning-project

data-science-notebook

:book: 每一个伟大的**和行动都有一个微不足道的开始

data-science-question-answer

A repo for data science related questions and answers

data-science-self-review

Summary of Data Science Topics

data-science-study-materials

"Big data is at the foundation of all the megatrends that are happening." – Chris Lynch

data-scientist-mooc

Coursera class in data science using R

data-structures

COMP 15: data structures. Topics include arrays, linked lists, trees, graphs, dynamic storage allocation, recursion, and sorting.

data-structures-1

Course Data structures December 2018 - SoftUni. Custom implementations of the most used data structures.

data-structures-algorithms

COMPSCI 187: Data Structures and Algorithms. Topics include arrays, linked lists, trees, graphs, dynamic storage allocation, recursion, and sorting.

data-structures-and-algorithms

:book::computer: A compendium for self-education geared for "people who do not have computer science degrees."

data-structures-and-algorithms-1

Solutions and sample code from "Data structures and algorithms" course in Sofia University, Faculty of Mathematics and Informatics

data-technology-books

"One person's data is another person's noise." ― K.C. Cole

data_sci_guide

data_science

Data visualization, TensorFlow architecture with deep_asteroid project , examples and basics

data_science_capstone

data_structures

C++ Data Structures and a few simple projects!

data_structures_and_algorithms

database-books

"Computing should be taught as a rigorous - but fun - discipline covering topics like programming, database structures, and algorithms. That doesn't have to be boring." -- Geoff Mulgan

database-fundamentals

Software University - C# DB Fundamentals (Courses: DB Basics MS SQL, DB Advanced Entity Framework Core)

databases-advanced-entityframework-core

This repository contains projects and solutions from "Databases Advanced - Entity Framework - February 2019" course at SoftUni.

databases-basics-mssql-server

Course Databases Basics MSSQL Server January 2019 - SoftUni.

datacleaning-basic-feature-engineering-techniques-to-the-regression-dataset.

Basic feature engineering techniques to the regression dataset. To-do list: 1. Import the necessary libraries. 2. Import the dataset (final_dataset.csv) 3. Remove columns with missing values greater than 40% of dataset size. 4. Extract numeric data from columns property_price, square_area & carpet_area using regular expressions. Make sure that units are standardized (all the values in property_price should be in lakhs) 5. In the above columns, fill empty values with mean of remaining data points 6. Convert columns facing, overlooking, ownership, transaction, furnishing into categorical variables by assigning values [0,1,2…]. 7. In the above columns, fill empty values with 0. 8. Convert all values in the floor column to decimals. For example, convert “10 out of 14 floors” as 10/14 = 0.71. 9. Fill empty values in floor and balcony with 0.

datascience_interview_questions

My Solutions to 120 commonly asked data science interview questions.

datasciencecoursera

Data Science Repo and blog for John Hopkins Coursera Courses. Please let me know if you have any questions.

datasciencecoursera-1

Coursera DataScience

datascienceinterview

Interview stuff for friends

datasciencespcoursenotes

Compiled Notes for all 9 courses in the Coursera Data Science Specialization

dataset-dimensionality-reduction-python

Here I've demonstrated how and why should we use PCA, KernelPCA, LDA and t-SNE for dimensionality reduction when we work with higher dimensional datasets.

datasharing

The Leek group guide to data sharing

datavisualizationlab

Solutions to exercises from Data Visualization Lab