Kapil Sachdeva
"Work like Hell. Share all you know. Abide by your handshake. Have fun!" - Dan Geer
I saw this on my mentor’s internal profile page some 20 years back, I shamelessly stole it and made it mine .... years later I discovered Dan Geer, the author of this quote ...but it does not matter who said it, rather the key is to assimilate these adages, these words of wisdom in your very being and is equally important to keep them in your sight as the gentle reminder of what is important!
Amongst the many obligations and responsibilities that we all have, the one that remains most dear to me is to keep learning and then sharing what I learned. I have done this for as long as I can remember; very early on in my life, I had accidentally discovered that you learn more when you share what you know. This is one aspect of my life that has been very consistent & the one I cherish the most.
This youtube channel is my new medium of sharing what "I think I know"!
Cryptography 101 - Bob and Alice's Love Story
Eliminate Grid Sensitivity | Bag of Freebies (Yolov4) | Essentials of Object Detection
GIoU против DIoU против CIoU | Потери | Основы обнаружения объектов
Пирамидальная сеть признаков | Шея | Основы обнаружения объектов
Bounding Box Prediction | Yolo | Essentials of Object Detection
Anchor Boxes | Essentials of Object Detection
Intersection Over Union (IoU) | Essentials of Object Detection
A Better Detection Head | Essentials of Object Detection
Detection Head | Essentials of Object Detection
Reshape,Permute,Squeeze,Unsqueeze made simple using einops | The Gems
Image & Bounding Box Augmentation using Albumentations | Essentials of Object Detection
Bounding Box Formats | Essentials of Object Detection
Object Detection introduction and an overview | Essentials of Object Detection
Softmax (with Temperature) | Essentials of ML
Grouped Convolution - Visually Explained + PyTorch/numpy code | Essentials of ML
Convolution, Kernels and Filters - Visually Explained + PyTorch/numpy code | Essentials of ML
Matching patterns using Cross-Correlation | Essentials of ML
Let's make the Correlation Machine | Essentials of ML
Трюк с репараметризацией — ПОЧЕМУ И ОБЪЯСНЕНИЕ СТРОИТЕЛЬНЫХ БЛОКОВ!
Variational Autoencoder - VISUALLY EXPLAINED!
Probabilistic Programming - FOUNDATIONS & COMPREHENSIVE REVIEW!
Metropolis-Hastings - VISUALLY EXPLAINED!
Цепи Маркова — НАГЛЯДНОЕ ОБЪЯСНЕНИЕ + История!
Monte Carlo Methods - VISUALLY EXPLAINED!
Сопряженная априорная терапия — применение и ограничения ЯСНО ОБЪЯСНЕНЫ!
How to Read & Make Graphical Models?
Posterior Predictive Distribution - Proper Bayesian Treatment!
Sum Rule, Product Rule, Joint & Marginal Probability - CLEARLY EXPLAINED with EXAMPLES!
Noise-Contrastive Estimation - CLEARLY EXPLAINED!
Bayesian Curve Fitting - Your First Baby Steps!