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best_classifier

Classification models are used on a same data set to check accuracy of different models.

bitcoin-predcitor

bulls-eye

Here is an interesting game to guess a number between a range.

calculator-gui-

UI based simple calculator using Python Tkinter module, which can perform basic arithmatic operations addition, subtraction, multiplication and division.

cement-strength-

Regression through layers using keras

cloud-kitchen

finds best location to open swiggy/zomato like office in a city

clustering-on-vehicle-dataset

Imagine that 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.

co2-emission-estimator

co2emission

get co2 emmision of engine from engine details

color-color

In this game player has to enter color of the word that appears on the screen and hence the score increases by one, the total time to play this game is 30 seconds. Colors used in this game are Red, Blue, Green, Pink, Black, Yellow, Orange, White, Purple and Brown. Interface will display name of different colors in different colors. Player has to identify the color and enter the correct color name to win the game.

countdown-timer

5.4.3.2.1

credit-card-fraud-detection

customer-segmentation-

Imagine that you have a customer dataset, and you need to apply customer segmentation on this historical data. Customer segmentation is the practice of partitioning a customer base into groups of individuals that have similar characteristics. It is a significant strategy as a business can target these specific groups of customers and effectively allocate marketing resources. For example, one group might contain customers who are high-profit and low-risk, that is, more likely to purchase products, or subscribe for a service. A business task is to retaining those customers. Another group might include customers from non-profit organizations. And so on.

data-analysis

Data Anlysis NB

datascientist

dffml

The easiest way to use Machine Learning. Mix and match underlying ML libraries and data set sources. Generate new datasets or modify existing ones with ease.

drug-assignment

About the dataset Imagine that you are a medical researcher compiling data for a study. You have collected data about a set of patients, all of whom suffered from the same illness. During their course of treatment, each patient responded to one of 5 medications, Drug A, Drug B, Drug c, Drug x and y. Part of your job is to build a model to find out which drug might be appropriate for a future patient with the same illness. The feature sets of this dataset are Age, Sex, Blood Pressure, and Cholesterol of patients, and the target is the drug that each patient responded to.

fake-news-analyzer

fish-prediction

Predecits species of fish using fish dimensions

gravity

Sympy for solving gravitational force

hand-written-digit-classification

Classifies which handwritten digit it is

identify-behavior-patterns-via-smart-phone-sensor-data

Identifying Human Behavior patterns using data recorded from smartwatch

image-classifier-

Uses keras CNN model to classify images , tensorflow at backend

insurance-price_predictor

Regression model to predict insurance price of indivduals

iris-classification

logistic-telecommunication-

About the dataset We will use a telecommunications dataset for predicting customer churn. This is a historical customer dataset where each row represents one customer. The data is relatively easy to understand, and you may uncover insights you can use immediately. Typically it is less expensive to keep customers than acquire new ones, so the focus of this analysis is to predict the customers who will stay with the company. This data set provides information to help you predict what behavior will help you to retain customers. You can analyze all relevant customer data and develop focused customer retention programs. The dataset includes information about: Customers who left within the last month – the column is called Churn Services that each customer has signed up for – phone, multiple lines, internet, online security, online backup, device protection, tech support, and streaming TV and movies Customer account information – how long they had been a customer, contract, payment method, paperless billing, monthly charges, and total charges Demographic info about customers – gender, age range, and if they have partners and dependents

magic-calculator

calculator

movie-recommender

Content Based Recommender SystemNow, let's take a look at how to implement Content-Based or Item-Item recommendation systems. This technique attempts to figure out what a user's favourite aspects of an item is, and then recommends items that present those aspects. In our case, we're going to try to figure out the input's favorite genres from the movies and ratings given.

movie-recommender-collaborative-

news_virality

Crawl news & information websites & anticipate the likelihood of its virality.