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Python 3 solutions to HackerRank's RegEx challenges.

Python 3 solutions to HackerRank's Python challenges.

Adaline is a single-layer neural network, a variation of the original Perceptron architecture.

Using MobileNetV2 to classify Google's image dataset "cats and dogs".

TensorFlow deep regression model predicting bicycle rental.

Perceptron regressing revenue for an ice cream stand according to temperature.

PySpark for multiple linear regression on car horsepower using SMOTE for data augmentation.

Adaline regressor learning the Celsius to Fahrenheit formula.

MySQL solutions to HackerRank's SQL challenges.

PySpark with logistic regression predicting if customers will exit a bank service.

Competitive programming solutions (UVa, LeetCode, codeforces, InterviewBit, etc.).

Fully connected neural network analyzing sentiments in reviews for Amazon's Alexa.

Haar cascade classifiers detecting cars and persons in videos with OpenCV.

Haar cascade classifiers detecting faces and eyes in images with OpenCV.

Convolutional autoencoder removing noise from Fashion MNIST clothing images.

Convolutional autoencoder reducing traffic sign images to 1/6 of their original size.

Transferring MobileNetV2's feature extractor layers to classify flower images.

A quick analysis of simple CNN architectures classifying Handwritten MNIST dataset.

Simple CNN architecture classifying Fashion MNIST.

4-layer neural network on house price linear regression.

Using LeNet convolutional neural network to classify traffic signs images.

A simple Javascript pong game with the player's pad controlled by the mouse.

Graph-based clustering method that uses Prim and Kruskal algorithms to cluster.

Using TensorFlow API to transfer a ResNet-50 neural network and connect new fully connected layers to classify cats and dogs images.

Fully connected neural network diagnosing patients with diabetes.

A data science analysis using kNN and MLP algorithms on HOG image descriptors.