farzinshams.github.io

Personal projects on machine learning and data analysis.

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EDA and prediction of NYC's MTA subway data (EDA, Pandas, Facebook Prophet)

In this work, we explore NYC's MTA subway usage data and predict future number of passengers.

Code (English)

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Exploratory Data Analysis of the Brazilian Credit Operations Dataset (EDA, Pandas)

In this work, we plot several bar plots and pie charts to visually explore the dataset on brazil's credit operations.

Code (Portuguese)

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Service Level Agreement Prediction (Time Series, Regression)

In this work, we predict the service level agreement of february 28th using real data from a company (confidential) from january and february. Before doing the prediction, we had to convert the data to a time series format.

Code (Portuguese)

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Cifar-10 Classification (Transfer Learning, Keras)

In this work, we use SqueezeNet's architecture on the Cifar-10 dataset to study the influence of freezing different layers during training. SqueezeNet was originally trained on the ImageNet dataset.

Code
Report (Portuguese)

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Health Tweets Dataset Analysis (Unsupervised Learning: Kmeans++ and PCA)

In this work, we implement Kmeans++ and PCA from scratch to analyze tweets about health.

Code
Report (Portuguese)

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MNIST Autoencoder (Pytorch)

Using Pytorch to build an Autoencoder on the MNIST dataset.

Code (Portuguese)

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Fashion MNIST (Logistic, Multinomial Regression and Neural Networks Logistic Regression Implementation)

Implementing different types of models from scratch to classify the Fashion MNIST dataset.

Code
Report (Portuguese)

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Facial Keypoints Detection (Deep Learning, Pytorch, Regression)

Using deep learning to find facial keypoints on an image dataset.

Code

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Diamonds In-Depth Analysis (Linear Regression)

In this work, we explore different alternatives of linear regression on the Kaggle dataset Diamonds In-Depth Analysis and compare their performances.

Code
Report (English)