Creating a Kaggle Workflow: In this project, I tried to build a workflow for a sample of the Kaggle's projects (the sinking of the Titanic) so I can follow the same pattern for the other Kaggle projects in the future

Building A Handwritten Digits Classifier: In this project, I tried to use and compare the k-nearest neighbors algorithm and neural networks with different numbers of neurons and different hidden layers for classifying handwritten digits problem.

Predicting Bike Rentals: In this project, I have used and compared Linear Regression, Decision Tree Regression and Random Forest algorithms to predict bike rentals. I also tried to find the best parameters to prevent overfitting and get good results.

Predicting the stock market This project is about using the linear regression model to predict the daily price of the S&P500 Index. Making predictions only one day ahead is also practiced.

Predicting House Sale Prices: In this project, for predicting house prices feature engineering and feature selection with the combination of the linear regression model are used.

Predicting Car Prices: This project is about using the k-nearest neighbors algorithm to predict car prices.

Winning Jeopardy: In this project, a dataset of Jeopardy questions is used to figure out some patterns in the questions that could help to win.

Building a Spam Filter with Naive Bayes: In this project, a spam filter function is written using the multinomial Naive Bayes algorithm to classify SMS messages as spam and non-spam.

Mobile App for Lottery Addiction: A medical institute decides to build a mobile app to help lottery addicts to estimate the probability of winning. This project provides the engineering team of the institute some functions to calculate the requested probabilities.

Finding the best markets to advertise: In this project I help an elearning company to find the best market to advertise in based on the freeCodeCamp's 2017 New Coder Survey.

SAT scores of NYC schools and Demographics: This project analyzes New York City schools according to the SAT score and tries to find correlations between demographics like race, gender, class size, and more.

Star Wars Survey: This project is based on the Star Wars survey of FiveThirtyEight team. The ranking and number of views are analyzed based on some factors like gender, education, location, etc.

Dissatisfaction in Employee Exit Surveys: In this project, I work with exit surveys from two institutes in Queensland, Australia, and try to analyze if employees resigning due to some kind of dissatisfaction.