| Title |
Date |
| ML Basics #4: Replace Negatives With Zeros! |
|
| ML Basics #3: More Layers! |
|
| ML Basics #2: Multilayer Perceptron |
|
| The Autodidact's Register: Issue #1 |
|
| ML Basics #1: Start With A Neuron |
|
| Takeaways from Naval Ravikant's JRE episode |
|
| Using Service Accounts for GKE workloads |
|
| Book Summary: Atomic Habits |
|
| Understanding the A star algorithm |
|
| Summary Notes: Bayes' Theorem |
|
| Visualizing inputs that maximally activate feature maps of a convnet |
|
| Generating artistic images using Neural Style Transfer |
|
| Understanding Object Detection Part 4: More Anchors! |
|
| Understanding Object Detection Part 3: Single Shot Detector |
|
| Blogging Philosophy |
|
| Understanding Object Detection Part 2: Single Object Detection |
|
| Understanding Object Detection Part 1: The Basics |
|
| Evolution of Grad-CAM heat-maps along a ResNet-34 |
|
| Generating class discriminative heat-maps using Grad-CAM |
|
| Understanding ResNets |
|
| Word Embeddings and RNNs |
|
| Summary Notes: GRU and LSTMs |
|
| Summary Notes: Basic Recurrent Neural Networks |
|
| Visualizing Convolutions |
|
| Visualizing Optimisation Algorithms |
|
| Moving from Jekyll to Nikola |
|
| Summary Notes: Forward and Back Propagation |
|
| Writing a decision tree from scratch |
|
| Booking Wonder Woman tickets with a twist |
|