About the Bootcamp

A 3-day Machine Learning Bootcamp organised by Department of Electronics and Communication Engineering, Santhiram Engineering College (SREC) Nandyal in the dates of 25th - 27th November 2021. Team from madBlocks Academy will be joining the session to encourage students to work on Machine Learning applications.

About the Speaker

Madhu Parvathaneni alias MS is a Sloutions Architect at madBlocks ML/AI Group and Director & CEO at Madblocks Technologies Pvt Ltd. He has 10+ years of experience in building IoT products from prototype stage to production stage. He trained more than 1.8 lakh students and 10K+ faculties across India on various cutting-edge technologies like IoT, Machine Learning, Cloud Computing, Augmented and Virtual Reality, Robotics, Blockchain etc...

Softwares

Google Colab (Access Google Colab)
git (Download git)
Python (Download Python)

Day Wise Content

Day - 1:

Introduction to Machine Learning
git software
git commands
Data Pre-Processing Template
Data Gathering Techniques

Telegram Group

https://t.me/+_380Zk3IHHkxNWNl

Subscribe on our Youtube Channel

https://youtube.com/madblockstechnologies

Contact

Reach me on LinkedIn (Maddy)

Official Repo of my work for SREC Nandyal Machine Learning Bootcamp

Related tags

Overview

About the Bootcamp

About the Speaker

Softwares

Day Wise Content

Telegram Group

Subscribe on our Youtube Channel

Contact

Owner

MS

This is the code for CVPR 2021 oral paper: Jigsaw Clustering for Unsupervised Visual Representation Learning

A library for differentiable nonlinear optimization.

Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+

This library contains a Tensorflow implementation of the paper Stability Analysis of Unfolded WMMSE for Power Allocation

FocusFace: Multi-task Contrastive Learning for Masked Face Recognition

🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

Official PyTorch implementation of "RMGN: A Regional Mask Guided Network for Parser-free Virtual Try-on" (IJCAI-ECAI 2022)

Pytorch implementation for the Temporal and Object Quantification Networks (TOQ-Nets).

How to use TensorLayer

Code for ACL2021 long paper: Knowledgeable or Educated Guess? Revisiting Language Models as Knowledge Bases

Data cleaning, missing value handle, EDA use in this project

[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing

The FIRST GANs-based omics-to-omics translation framework

DeOldify - A Deep Learning based project for colorizing and restoring old images (and video!)

Scripts for training an AI to play the endless runner Subway Surfers using a supervised machine learning approach by imitation and a convolutional neural network (CNN) for image classification

CATE: Computation-aware Neural Architecture Encoding with Transformers

Try out deep learning models online on Google Colab

DSTC10 Track 2 - Knowledge-grounded Task-oriented Dialogue Modeling on Spoken Conversations

Deep Image Search is an AI-based image search engine that includes deep transfor learning features Extraction and tree-based vectorized search.