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Deploy an Image Classification Model Using Flask
Introduction to Computer Vision
Reading and Stacking Images Understanding Colorspaces Image Processing Edge Detection Blur Detection Image Operations HOG features SIFT features Camera Calibration Interesting Applications of OpenCV
Why Do We Need CNN? How Does Filters Work in CNN? Parameter Sharing and Local Connectivity in CNN Understanding CNN Architecture What is Pooling in CNN? Math Behind Convolutional Neural Networks Image Classification Tutorial using CNN Introduction to Separable Convolutions
Introduction to Transfer Learning
CNN Visualization
LeNet AlexNet VGG16 Implement VGG Dataloaders using Pytorch Implementing VGG16 using Dataloaders
Understanding Inception Modules
Understanding Residual Blocks Building Your Own Residual Block from Scratch Understand ResNet 34 Build ResNet34 from Scratch With Python! Different Versions of ResNet
Understanding the Architecture of DenseNet
Implement Crowd Counting using CSRNet
Introduction to Object Detection Bounding Box Evaluation: (Intersection over union) IOU Calculating IOU
Why do we need Region Based Convolulional Neural Network? Fast R-CNN and Faster R-CNN Building Social Distancting Tool using Faster R-CNN
Single Shot Detector SSD Custom Object Detection on the browser using TensorFlow.js YOLOv1 Other Versions of YOLO (v2 and v3) YOLOv3 YOLOv4 YOLOv5 YOLOv7 RetinaNet
DETR
Introduction to Face Detection Why is Face Alignment Important for Face Recognition? Implementing Face Detection
Introduction to Object Tracking Object Tracking Applications
Comprehensive Guide on Pose Estimation Implement Human Pose Estimation
Introduction to Image Segmentation Different Types of Image Segmentation Implementing Background removal Image Segmentation Algorithms
Unet DeepLabv3 Mask R-CNN Architecture
Build Your Own Video Classification Model
Introduction to Image Generation What are Generative models? Understanding GANs Implementing Texture Generation using GANs Better GAN Architectures
Few Shot Learning

Data Hackathon by Analytics Vidhya & GL, Gurgaon, India, 24th May 2015

A
Analytics Vidhya Last Updated : 14 May, 2015
2 min read

Introduction

Every data scientist/business analyst or anyone who is tenaciously working hard to rise up the ladder of success in analytics industry, wants to build his/her portfolio by solving kaggle questions. Unfortunately, not everyone succeeds in solving it. Eventually,  people get demotivated and succumbs to inaction.

To convert this failure into a success, Analytics Vidhya is organizing Data Hackathon where some determined brains from across the country will come and solve a kaggle competition by forming a team.

This session will be steered by Mr. Kunal Jain, Data Scientist, Growth Hacker.

Data Hackathon, Analytics Vidhya, Gurgaon, IOT

 

 Why should you attend this?

1. If you want to know about the best tips & tricks to successfully solve kaggle questions, you should attend this.

2. If you are striving for self-evaluation, knowing your strength and weakness, you should attend this. You will understand and realize the weak points where you are struggling and how you can improve.

3. If you are looking to explore analytics in depth, this can be an ideal platform for you. You will get the chance to compete with best brains in data analytics around your area and get the inspiration to move a step ahead of where you are standing now.

4. Needless to say, this is going to be a great place for networking.

 

If these reasons excites you enough, you can register for Data Hackathon here.

 

Contact

Here are some important details:

Date – 24th May 2015

Venue – Great Lakes Institute of Management, 815, Udyog Vihar, Phase V, Gurgaon, Haryana, India (Nearest Metro Station is Indusland Rapid Metro)

P.S – After receiving numerous requests, we will also be organizing Data Hackathon in Bangalore, Kolkata and Mumbai. Below are the links for registration:

Bangalore, 17th May 2015: Click here

Mumbai, date to be announced: Click here

Kolkata, date to be announced: Click here

 

For more information & details on these meetups, feel free to drop us a mail at [email protected] or you can also reach us at 0124-4264086.

A
Analytics Vidhya

Analytics Vidhya Content team

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