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terraformer

CLI tool to generate terraform files from existing infrastructure (reverse Terraform). Infrastructure to Code

tfenv

Terraform version manager

the-complete-sql-bootcamp

SQL challenges using PostgreSQL 9.6 in pgAdmin 4 from "The Complete SQL Bootcamp" Udemy course by Jose Portilla

the-python-mega-course-build-10-real-world-applications-

The Python Mega Course is one of the top online Python courses with over 100,000 enrolled students and is targeted toward people with little or no previous programming experience. The course follows a modern-teaching approach where students learn by doing. You will start Python from scratch by first creating simple programs. Once you learn the basics you will then be guided on how to create 10 real-world complex applications in Python 3 through easy video explanations and support by the course instructor. Some of the applications you will build during the course are database web apps, desktop apps, web scraping scripts, webcam object detectors, web maps, and more. These programs are not only great examples to master Python, you can also use any of them as a portfolio once you have built them. By buying the course you will gain lifetime access to all its videos, coding exercises, quizzes, code notebooks, and the Q&A inside the course where you can ask your questions and get an answer the same day. On top of that you are covered by the Udemy 30-day money back guarantee, so you can easily return the course if you don't like it. If you don't know anything about Python, do not worry! In the first two sections, you will learn Python basics such as functions, loops, and conditionals. If you already know the basics, then the first two sections can serve as a refresher. The other 22 sections focus entirely on building real-world applications. The applications you will build cover a wide range of interesting topics: Web applications Desktop applications Database applications Web scraping Web mapping Data analysis Data visualization Computer vision Object-Oriented Programming Specifically, the 10 Python applications you will build are: A program that returns English-word definitions A program that blocks access to distracting websites A web map visualizing volcanoes and population data A portfolio website A desktop-graphical program with a database backend A webcam motion detector A web scraper of real estate data An interactive web graph A database web application A web service that converts addresses to geographic coordinates To consider yourself a professional programmer you need to know how to make professional programs and there's no other course that teaches you that, so join thousands of other students who have successfully applied their Python skills in the real world. Sign up and start learning Python today! What you’ll learn Go from a total beginner to an advanced-Python programmer Create 10 real-world Python programs (no useless programs) Solidify your skills with bonus practice activities throughout the course Create an app that translates English words Create a web-mapping app Create a portfolio website Create a desktop app for storing book information Create a webcam video app that detects objects Create a web scraper Create a data visualization app Create a database app Create a geocoding web app Create a website blocker Send automated emails Analyze and visualize data Use Python to schedule programs based on computer events. Learn OOP (Object-Oriented Programming) Learn GUIs (Graphical-User Interfaces) Are there any course requirements or prerequisites? A computer (Windows, Mac, or Linux). No prior knowledge of Python is required. No previous programming experience needed. Who this course is for: Those with no prior knowledge of Python. Those who know Python basics and want to master Python

the_evolution_of_gradient_descent

This is the code for "The Evolution of Gradient Descent" by Siraj Raval on Youtube

thing-tracker-site-template

A template for a simple site to participate in the Thing Tracker Network.

thinkpython2

LaTeX source and supporting code for Think Python, 2nd edition, by Allen Downey.

threadpool

Parallel Processing in R using a Thread Pool

time-series-analysis

This forecasts the number of Views, distinct Users and Analytics in Spotfire using the last 9 years data. Forecasting is done using ARIMA Model.

time-series-forecasting

Code to 1) scrap wikipedia page view counts, and to 2) conduct time series analysis with GAM

timeseriesanalysiswithpython

timeseriesforecasting

Material for the Time Series Forecasting article

traffic-accident-analysis

Traffic Accident Analysis using python machine learning

traffic_prediction

Traffic Prediction in PaddlePaddle (ASC17 Deep Learning Application)

trump-lies

Tutorial: Web scraping in Python with Beautiful Soup

turtle

Python reverse shell.

tutorial-lambda-basico

Tutorial Lambda Básico do Canal do Um Inventor Qualquer

tutorial-python-brasil

Construindo API's robustas utilizando Python

tutorial-version-control

tutorial de como fazer controle de versão de projetos ou códigos utilizando o git + github

tutorialensemble

Arquivos para o tutorial do artigo Tutorial: Aumentando o Poder Preditivo de Seus Modelos de Machine Learning com Stacking Ensembles

twitter-api-v2-sample-code

Sample code for the Twitter API early access endpoints (Python, Java, Ruby, and Node.js).

twitter-sentiment-analysis---analytics-vidhya

Problem Statement The objective of this task is to detect hate speech in tweets. For the sake of simplicity, we say a tweet contains hate speech if it has a racist or sexist sentiment associated with it. So, the task is to classify racist or sexist tweets from other tweets. Formally, given a training sample of tweets and labels, where label '1' denotes the tweet is racist/sexist and label '0' denotes the tweet is not racist/sexist, your objective is to predict the labels on the test dataset. Motivation Hate speech is an unfortunately common occurrence on the Internet. Often social media sites like Facebook and Twitter face the problem of identifying and censoring problematic posts while weighing the right to freedom of speech. The importance of detecting and moderating hate speech is evident from the strong connection between hate speech and actual hate crimes. Early identification of users promoting hate speech could enable outreach programs that attempt to prevent an escalation from speech to action. Sites such as Twitter and Facebook have been seeking to actively combat hate speech. In spite of these reasons, NLP research on hate speech has been very limited, primarily due to the lack of a general definition of hate speech, an analysis of its demographic influences, and an investigation of the most effective features. Data Our overall collection of tweets was split in the ratio of 65:35 into training and testing data. Out of the testing data, 30% is public and the rest is private. Data Files train.csv - For training the models, we provide a labelled dataset of 31,962 tweets. The dataset is provided in the form of a csv file with each line storing a tweet id, its label and the tweet. There is 1 test file (public) test_tweets.csv - The test data file contains only tweet ids and the tweet text with each tweet in a new line.

typeshed

Collection of library stubs for Python, with static types

udacity-data-engineering-projects

Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.

udacity-data-engineering-projects-1

My solutions for the Udacity Data Engineering Nanodegree

udacity-dataanalyticsnanodegree-portfolio

Overview of the Udacity Data Analyst Nanodegree

udacity-dend-project-3

Udacity Data Engineer Nano Degree - Project-3 (Data Warehouse)

udacity_ds_nanodg_blog_post

Repo containing the EDA and ML work for a data science blog post

ui

The home of the Prefect UI

updated-salesforce-tableau-crm-einstein-discovery-consultant-exam-dumps-for-beginners-to-prep