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agglomerative-clustering

average_true_range

Calculate and analyse the average true range as an indicator of volatility

black-scholes-model

This notebook develops the Black-Scholes Model for option pricing

covid-19-forecast

Forecast of new COVID-19 positive cases in The United Statets

dbscan-clustering

Density-based Clustering locates regions of high density that are separated from one another by regions of low density. Density, in this context, is defined as the number of points within a specified radius.

decision-trees

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

drinking-habit-of-global-population

Analysis of alcohol consumption around the world to determine inventory levels of a wine a brewery establishment.

hello-world

First repository in GitHub

implied-volatility

Calculation of Implied volatility for options

k-means

In this notebook, learn how to use k-Means for customer segmentation.

knn-algorithm

Load a customer dataset related to a telecommunication company, clean it, use KNN (K-Nearest Neighbours) to predict the category of customers, and evaluate the accuracy of your model.

linear-regression

Learn how to use scikit-learn library to implement Simple linear regression with a data set that is related to fuel consumption and Carbon dioxide emission of cars.

logistic-regression

In this notebook, learn Logistic Regression, and then, create a model with telecommunications data to predict when its customers will leave for a competitor, so that you can take some action to retain the customer.

non-linear-regression

learn about non linear regressions and apply an example on python. In this notebook, we fit a non-linear model to the data points corresponding to China's GDP from 1960 to 2014.

predicting-the-winning-college-basketball-team

In this notebook, I apply different classification algorithms to predict the winner for the basketball tournament.

python-for-finance-assessment

python assessment

python-in-depth

Python course covering all basic concepts - This are a series of python exercises

python-random-quote

A file-based quote bot written in Python

ruby-course

An introduction to Ruby

scraping-and-analyzing-basketball-statistics-with-python

In this notebook, I web scrape basketball statistics from Wikipedia of some of the greatest basketball players. I also perform analyses on the data using Pandas, plot, data answer some basic questions then store the data on the IBM cloud.

sp500-day-trading-analysis

Analysis of daily return distribution on the S&P500 for the last 50 years.

stock_forecast_bm

Stock price forecast using Monte Carlo simulation

support-vector-machine

In this notebook, Use SVM (Support Vector Machines) to build and train a model using human cell records, and classify cells to whether the samples are benign or malignant.

visualizing-data-with-python

Learn how to create interesting graphics and charts and customize them to make them more effective and more pleasing to your audience.