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This repo contains submissions of all assignments of a EVA by TSAI

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Sushmitha-Katti/EVA-4

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EVA-4

This repo contains all the assignments from the course called EVA conducted by the 'The School Of AI'. Object detection, Object reconisation, segmentation, monocular depth estimation.

  1. Basics of Python - link
  2. Setting Up Basic Skeleton - link
  3. Pytorch Basics - link
  4. To achive 99.4% validation accuracy for MNIST DatSet - link
  5. The whole process- Coding drill - link
  6. Regularisation techinques on MNIST - link
  7. Advanced convolutions(depthwise seperable and dialated convolutions) on CIFAR 10 - link
  8. 85%+ Validation accuracy target for CIFAR 10 -link
  9. 87%+ Validation accuracy target using Albumentation library for agumentation. -link
  10. 88%+ Validation accuracy target using Reduce Lr On Pleateau and Implentaion Of Lr finder - link
  11. Introduction Of SuperConvergence and 90%+ accuracy for CIFAR dataset using One Cycle Policy - link
  12. Prediction best no of bounding box for 50 dog images and Training TinyImageNetData on RESNet 18 and achive 50%+ accuracy. link
  13. YoloV3 implementation on Custom created dataset via transfer learning - link
  14. Dataset Creation for Monocular depth Estimation and Segmentation - link
  15. Final Assignment - Monocular depth Estimation and Segmentation - link

PytNet - Contains all the functions used for these assignment. Custom library built on top of Pytorch. - link