ramasravani Goto Github PK

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ramasravani's Projects

dslabs

Data Science Labs R package: includes functions and data for data science courses

fastai

The fastai deep learning library, plus lessons and tutorials

foundations-for-big-data-analysis-with-sql

In this course, you'll get a big-picture view of using SQL for big data, starting with an overview of data, database systems, and the common querying language (SQL). Then you'll learn the characteristics of big data and SQL tools for working on big data platforms. You'll also install an exercise environment (virtual machine) to be used through the specialization courses, and you'll have an opportunity to do some initial exploration of databases and tables in that environment. By the end of the course, you will be able to • distinguish operational from analytic databases, and understand how these are applied in big data; • understand how database and table design provides structures for working with data; • appreciate how differences in volume and variety of data affects your choice of an appropriate database system; • recognize the features and benefits of SQL dialects designed to work with big data systems for storage and analysis; and • explore databases and tables in a big data platform. To use the hands-on environment for this course, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements: • Windows, macOS, or Linux operating system (iPads and Android tablets will not work) • 64-bit operating system (32-bit operating systems will not work) • 8 GB RAM or more • 25GB free disk space or more • Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled; on Windows and Linux computers, you might need to enable it in the BIOS) • For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work)

freecodecamp

The https://freeCodeCamp.org open source codebase and curriculum. Learn to code for free together with millions of people.

gatsby-uipath

Build blazing fast, modern apps and websites with React

github-demo

A simple demo repository to show the basic Git workflow

go

The Open Source Data Science Masters

gt-nlp-class

Course materials for Georgia Tech CS 4650 and 7650, "Natural Language"

hackerrankpractice

170+ solutions to Hackerrank.com practice problems using Python 3 and Oracle SQL

hadoop

Mirror of Apache Hadoop

hadoop-book

Example source code accompanying O'Reilly's "Hadoop: The Definitive Guide" by Tom White

hadoop-book-1

'Hadoop illuminated' hadoop book

healthcareai-py

Python tools for healthcare machine learning

hitchhikers-guide

The Hitchhiker's Guide to Data Science for Social Good

homemade-machine-learning

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

industry-machine-learning

A curated list of applied machine learning and data science notebooks and libraries across different industries.

jekyll

:globe_with_meridians: Jekyll is a blog-aware static site generator in Ruby

jukebox

Code for "Jukebox: A Generative Model for Music"

kaggle-learning

Repository for sharing the knowledge from the learning path of Kaggle Learning. All contributions welcome :).

kepler.gl

Kepler.gl is a powerful open source geospatial analysis tool for large-scale data sets.

learn_computer_science_in_5_months

This is the Curriculum for "Learn Computer Science in 5 Months" By Siraj Raval on Youtube

learn_data_science_in_3_months

This is the Curriculum for "Learn Data Science in 3 Months" By Siraj Raval on Youtube

learn_deep_learning_in_6_weeks

This is the Curriculum for "Learn Deep Learning in 6 Weeks" by Siraj Raval on Youtube

learn_machine_learning_in_3_months

This is the code for "Learn Machine Learning in 3 Months" by Siraj Raval on Youtube

learn_math_fast

This is the Curriculum for "How to Learn Mathematics Fast" By Siraj Raval on Youtube

lectures

Oxford Deep NLP 2017 course

lede-algorithms

Algorithms course materials for the Lede program at Columbia Journalism School

locality-sensitive-hashing

Application of Locality Sensitive Hashing to Audio Fingerprinting

machine-learning-course

:speech_balloon: Machine Learning Course with Python

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