Interview Prep
Career
GenAI
Prompt Engg
ChatGPT
LLM
Langchain
RAG
AI Agents
Machine Learning
Deep Learning
GenAI Tools
LLMOps
Python
NLP
SQL
AIML Projects

Reading list

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

The DataHour: Writing Reproducible Pipelines for Training Neural Networks

D
Dhruv Last Updated : 23 Jun, 2022
2 min read

Hey Readers,

We’re getting Andrey Lukyanenko, Kaggle Grandmaster, on board to lead an interactive DataHour session with us. He is working as a Senior Data Scientist with the IT consulting and solutions firm Careem. He has more than ten years of extensive experience in the field of analytics and data science. He will be explaining the Neural Networks, Writing Reusable and Reproducible Pipelines for Training Neural Networks. So, book your seat now! We know you don’t want to experience FOMO.

The DataHour

BOOK YOUR SEAT NOW! 🛋️

 

About the DataHour

Data science is concerned with reproducibility and companies all over the world are investing heavily to explore and build data science applications.

In this DataHour, Join Andrey demonstrating a working deep learning training pipeline using PyTorch-lightning as a wrapper for PyTorch code and Hydra for configuration file management.

 

About the Speaker

Andrey Lukyanenko works as a Senior Data Scientist for the IT solutions and consulting firm Careem. He has more than ten years of extensive experience in the field of analytics and data science. He wants to create Deep Learning apps that could benefit users and customers by making their lives better while also adding value to the business.

He is the Grandmaster of Kaggle Notebooks (ranked first in the kernel ranking), Kaggle Discussions, and Kaggle Competitions.

Prerequisites

A passion for understanding data science and a working mastery of both machine learning and Python.

Who is this DataHour for?

  • Those students interested in a career in data science
  • Professionals in data science who want to advance more quickly

Any Questions?

Email us at [email protected], or you can chat with the speaker directly during the session.

Conclusion

Register for the DataHour Here to take advantage of this wonderful opportunity.

Visit our YouTube Channel to view the recordings if you missed any of the previous episodes of “The DataHour.” On our blog, you may read a summary of the DataHour sessions that have already been held Here.

Connect

If you’re having trouble enrolling or would like to meet with us. Contact us at [email protected]

BOOK YOUR SEAT NOW! 🛋️

 

Data Science pipelinesdeep learningneural networkspytorchThe DataHour
D
Dhruv

Free Courses

Generative AI 4.7

Generative AI - A Way of Life

Explore Generative AI for beginners: create text and images, use top AI tools, learn practical skills, and ethics.
Large Language Models 4.5

Getting Started with Large Language Models

Master Large Language Models (LLMs) with this course, offering clear guidance in NLP and model training made simple.
Prompt Engineering 4.6

Building LLM Applications using Prompt Engineering

This free course guides you on building LLM apps, mastering prompt engineering, and developing chatbots with enterprise data.
LlamaIndex 4.8

Improving Real World RAG Systems: Key Challenges & Practical Solutions

Explore practical solutions, advanced retrieval strategies, and agentic RAG systems to improve context, relevance, and accuracy in AI-driven applications.
RAG systems using LlamaIndex 4.7

Microsoft Excel: Formulas & Functions

Master MS Excel for data analysis with key formulas, functions, and LookUp tools in this comprehensive course.

Recommended Articles

Responses From Readers

Clear

Write for us

Write, captivate, and earn accolades and rewards for your work
  • Reach a Global Audience
  • Get Expert Feedback
  • Build Your Brand & Audience
  • Cash In on Your Knowledge
  • Join a Thriving Community
  • Level Up Your Data Science Game
imag
Congratulations, You Did It!
Well Done on Completing Your Learning Journey. Stay curious and keep exploring!
Nikhil Mishra’s Journey to Becoming a Kaggle Grandmaster
Nikhil Mishra’s Journey to Becoming a Kaggle Grandmaster
The DataHour: Your Upcoming Learning Timeline
The DataHour: Your Upcoming Learning Timeline

We use cookies essential for this site to function well. Please click to help us improve its usefulness with additional cookies. Learn about our use of cookies in our Privacy Policy & Cookies Policy.

Show details