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1. Introduction_Data_Engineering_Machine_Learning Introduction_Data_Engineering_Machine_Learning Public

   This module is part of the Master's course and has imparted knowledge on mathematical and coding skills for developing machine learning applications using supervised algorithms as well as laid stro…

   Jupyter Notebook 1

2. Artificial_Intelligence_Machine_Learning Artificial_Intelligence_Machine_Learning Public

   Acquired in depth understanding on Theory of Generalization, model complexity and VC bound; recognize and manage under- & overfitting along with regularization; applied non-linear transformation to…

   Jupyter Notebook

3. Computer-Vision-Machine-Vision Computer-Vision-Machine-Vision Public

   Equipped knowledge on classical Machine Vision and Image Processing techniques by familiarizing with basics of digital images, convolution and sampling 2D images, linear and non-linear methods to f…

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4. DQN_MountainCar DQN_MountainCar Public

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5. Probabilistic-and-Explainable-AI Probabilistic-and-Explainable-AI Public

   Introduced to Probabilistic Programming, Probability Theory, Probabilistic Artificial Intelligence; to define probabilistic AI models ( using modeling formalism like generalized linear models, neur…

   Jupyter Notebook

6. Theory-and-Practice-of-Advanced-AI-Ecosystems Theory-and-Practice-of-Advanced-AI-Ecosystems Public

   Introduced to AWS: Cloud Foundations included cloud concepts, economics & billing, AWS global infrastructure, cloud security, networking & content delivery, compute, storage, databases, cloud archi…

   Python