My Journey with Deep Learning and Computer Vision

Index of blog posts for easy access.

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• Transfer Learning for Segmentation Using DeepLabv3 in PyTorch

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• Setting up a project in VS2019 and LibTorch1.6

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• Back-propagation Demystified [Part 1]: Back-propagation and Computational graphs
• Back-propagation Demystified [Part 2]: Computational graphs in Pytorch
• Back-propagation Demystified [Part 3]: Computational graphs in Tensorflow

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• Maxima vs Minima and Global vs Local: Basics of maxima, minima, local and global.
• Gradient Descent Optimization [Part 1]: Gradient descent explanation
• Gradient Descent Optimization [Part 2]: Python 1D and 2D example
• Gradient Descent Optimization [Part 3]: SGD, Mini batch and Batch SGD

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• Bias Variance Trade-off [Part 1]: Learn about bias, variance, over-fitting, under-fitting.

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• Image Data Generators in Keras: Learn how to construct a data pipeline in Keras/TensorFlow

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• Convolutions Convoluted? Nah: Convolutions explanation

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• Deep Learning: Our journey begins

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