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2020-us-election_twitter-sentiment-analysis

Produce polarity scores for each tweet with #2020 US Presidential Election hashtags to analyse, and visualize people's Positive, Negative and Neutral reactions to the 2020 US Presidential Election on Twitter using NLTK , Plotly and WordCloud libraries.

aws-deepracer-2020

Autonomous car model driven by reinforcement learning for the 2020 AWS DeepRacer League

china-gdp-non-linear-regression-analysis

China's GDP from 1960 to 2014 Non-Linear Regression model

covid-19-vs-world-happiness_data-analysis

Merge COVID19 dataset, published by John Hopkins University, which consists of the data related to the cumulative number of confirmed cases with World Happiness dataset consisting of various life factors, scored by the people living in each country around the globe in each Country, to see if there is any relationship between the spread of the virus in a country and how happy people are, living in that country.

covid-19_twitter-sentiment-analysis

Apply sentimental analysis on the tweets with covid19 hashtags to see people's reactions to the pandemic. Visualize tweets as Positive, Negative, and Neutral using NLTK label.

drugs-classification-decision-tree

Classification Decision Tree algorithm to build a model from historical data of patients, and their response to different medications. Then use the trained decision tree to predict the class of a unknown patient, or to find a proper drug for a new patient.

human-like_conversation_with_vocal-assistants

jhu-csse-covid-19-data-analysis

COVID19 Data Analysis, Visualizations and Predictions using 2019-nCoV Data Repository by Johns Hopkins CSSE.

movie_recommender

MovieLens based recommender system.使用MovieLens数据集训练的电影推荐系统。

moviegeek

A django website used in the book Practical Recommender Systems to illustrate how recommender algorithms can be implemented.

the-battle-of-the-neighborhoods-lyon_vs_world

traktforvlc

Automatically trakt.tv what you're watching on VLC

traktoid

Traktoid, a Trakt client for Android

vehicle-hierarchical-clustering

An automobile manufacturer has developed prototypes for a new vehicle. Before introducing the new model into its range, the manufacturer wants to determine which existing vehicles on the market are most like the prototypes--that is, how vehicles can be grouped, which group is the most similar with the model, and therefore which models they will be competing against. Our objective here, is to use clustering methods, to find the most distinctive clusters of vehicles. It will summarize the existing vehicles and help manufacturers to make decision about the supply of new models.

vimsheet

Vim cheat sheet from beginners to pros