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applications-of-data-science

Programming assignments to demonstrate the Applications of Data Science. These were completed as part of the Plaksha Tech Leaders Fellowship program.

coursera_deep_learning_specialization

Implementation of Logistic Regression, MLP, CNN, RNN & LSTM from scratch in python. Training of deep learning models for image classification, object detection, and sequence processing (including transformers implementation) in TensorFlow.

coursera_generative_adversarial_networks_specialization

coursera_natural_language_processing_specialization

Implementation of state-of-the-art NLP models using transformers for tasks including machine translation, text-summarization, chatbots, and question answering.

coursera_tensorflow_advanced_techniques_specialization

Used the Functional API to built custom layers and non-sequential model types in TensorFlow, performed object detection, image segmentation, and interpretation of convolutions. Used generative deep learning including Auto Encoding, VAEs, and GANs to create new content.

data_science

Data analysis & visualization of "2020 Kaggle Machine Learning & Data Science Survey" to highlight the tools and best practices used by the Data Science Practitioners along with a blog post on Medium.

disaster-response-nlp-pipeline

End-to-end machine learning pipeline to classify disaster messages into 36 categories and a web app to deploy the trained model.

dog_breed_classifier

End-to-end deep learning pipeline to classify images of dogs and humans to determine what breed the human or dog most resembles

machine-learning-lab-plaksha

Programming assignments covering fundamentals of machine learning and deep learning. These were completed as part of the Plaksha Tech Leaders Fellowship program.

machine_learning_udacity

recommendation_systems