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Kunjan Mhaske's Projects

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📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

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A curated list of articles that cover the software engineering best practices for building machine learning applications.

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Bag of Words model using SIFT (Scale-Invariant Feature Transform – 128 dimension vector) from OpenCV library to get features of images and cluster them using KMeans from sklearn library to create vocabulary of words for each type of images.

fashion-mnist-model-using-cnn-from-pytorch icon fashion-mnist-model-using-cnn-from-pytorch

Fashion-MNIST model to detect the types of clothes using 2D Convolutional Neural Networks and Linear Transformations from PyTorch-gpu library with Cross Entropy as a Loss function, ReLu activation function and Adam optimizer for training the model.

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The Open Source Data Science Masters

ml-coursera-python-assignments icon ml-coursera-python-assignments

Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.

obstacle-and-lane-detection-using-computer-vision icon obstacle-and-lane-detection-using-computer-vision

Applied YOLO model trained on COCO dataset to detect obstacles and Lane-Net model trained on tusimple.ai dataset for end-to-end lane detection. • Improved usability and response time by 50% using the combination and optimization of legacy codes of algorithms in assisted driving.

risky-loan-prediction-using-ml-in-r-studio icon risky-loan-prediction-using-ml-in-r-studio

Implemented and compared Random Forest, Decision Tree, KNN, SVM, and Logistic Regression outcomes with a confusion matrix. Concluded that Random Forest achieved the highest accuracy of 85% to predict the loan status for investors.

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AWiFS Dataset image processing python scripts to detect water bodies and burnt areas from multi-spectral sensor images.

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K12 Schools and University Search Web Applications (Contains APIs and Frontend code using Node JS, Sequelize ORM, React JS, and MySQL)

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Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

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