Resource Bank of Computer Vision, Natural Langauge Processing and MLops
This initiative compiles educational resources on a daily basis, making it possible for users to get all the data they want in one place.
♾️ 95% Data Science Skills Covered Course
Sr.No |
Courses |
Link |
1 |
Machine Learning Specialization |
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2 |
Deep Learning Specialization |
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3 |
Natural Language Processing Specialization |
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4 |
TensorFlow Developer Professional Certificate |
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5 |
TensorFlow: Advanced Techniques Specialization |
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6 |
TensorFlow: Data and Deployment Specialization |
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7 |
Machine Learning Engineering for Production (MLOps) Specialization |
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8 |
Generative Adversarial Networks (GANs) Specialization |
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9 |
Practical Data Science on the Amazon Web Services (AWS) Cloud Specialization |
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10 |
Mathematics of Data Science |
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11 |
** ** |
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Extra Resources
Sr.No |
Resource Name |
Link |
1 |
Intro to optimization in deep learning: Gradient Descent |
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2 |
ML system design usecases |
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2 |
Free datasets for Data Science, Data Analytics, and ML projects |
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3 |
Accuracy and Loss: Things to Know about The Top 1 and Top 5 Accuracy |
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4 |
** ** |
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5 |
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6 |
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Computer Vision Learning Path Recommended by OpenCV
Sr.No |
Book Name |
Link |
1 |
Computer Vision: Algorithms and Applications |
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2 |
Practical Deep Learning for Cloud, Mobile & Edge |
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3 |
Concise Computer Vision: An Introduction into Theory and Algorithms |
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4 |
Computer Vision: Principles, Algorithms, Applications, Learning |
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5 |
Computer Vision: Models, Learning, and Inference |
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6 |
Deep Learning for Vision Systems |
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7 |
Modern Computer Vision with Pytorch |
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8 |
Multiple View Geometry in Computer Vision |
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9 |
Learning OpenCV 5 Computer Vision with Python 3 |
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10. |
Computer Vision Metrics: Survey, Taxonomy, and Analysis |
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Articles
Sr.No |
Article Name |
Link |
1 |
Computer Vision: Algorithms and Applications |
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2 |
End to End Learning for Self-Driving Cars using python |
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3 |
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4 |
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5 |
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6 |
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7 |
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8 |
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9 |
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10 |
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Video
Sr.No |
Video Name |
Link |
1 |
Stanford Computer Vision playlist |
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2 |
Deep Learning for Computer Vision |
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3 |
Computer Vision (Andreas Geiger) |
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4 |
Deep Learning with PyTorch: Zero to GANs |
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5 |
Digital Image Processing |
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6 |
Image Signal Processing |
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7 |
The Geometry of vision |
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8 |
UCF Computer Vision Video Lectures 2012 |
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9 |
CAP5415 Computer Vision - Fall 2021 |
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10 |
UCF CRCV |
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11 |
Stanford Computer Vision |
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12 |
Deep Learning for Computer Vision |
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13 |
Deep Learning for Computer Vision |
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14 |
Image Processing with C++ |
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15 |
Full Stack Deep Learning - 2022 |
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16 |
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Extra Resources
Sr.No |
Resource Name |
Link |
1 |
Making Friends with Machine Learning |
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2 |
End to End Tutorial on CNN |
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3 |
Compact GPU Powerhouse |
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4 |
Machine Learning from Scratch - Python Tutorials |
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5 |
CUDA Crash Course |
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6 |
Object Tracking Using Deep SORT and YOLOv4 |
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7 |
Protecting Your Machine Learning Against Drift |
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8 |
LeetCode |
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9 |
Mathematics of Data Science |
|
10 |
Modern C++ (2021 Lecture & Tutorials) |
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11 |
Lecture: Modern C++ (Summer 2018, Uni Bonn) |
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12 |
Machine Learning |
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13 |
Krish naik youtuber |
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14 |
NPTEL MOOC Machine Learning 2016 |
|
15 |
Deep Learning |
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16 |
3Blue1Brown: Calculus |
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17 |
Learn TensorFlow and Deep Learning fundamentals with Python |
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18 |
GTC Sept 2022 Keynote with NVIDIA CEO Jensen Huang |
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19 |
ML Model Training and Inference with a Data Mesh |
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20 |
Attitude-Guided Loop Closure for Cameras with Negative Plane |
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21 |
CVonline: The Evolving, Distributed, Non-Proprietary, On-Line Compendium of Computer Vision |
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22 |
LearnopenCV |
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23 |
Expanding Language-Image Pretrained Models for General Video Recognition |
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24 |
Open-Set Semi-Supervised Object Detection |
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25 |
How To Deal with Dataset Bias |
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26 |
** ** |
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📝 NATURAL LANGUAGE PROCESSING
Learning Path NLP:
Credit : graykode
Books
Sr.No |
Book Name |
Link |
1 |
Natural Language Processing with Transformers, Revised Edition by Lewis Tunstall, Leandro von Werra, Thomas Wolf |
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2 |
Natural Language Processing with PyTorch Book by Brian McMahan and Delip Rao |
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3 |
Transformers for Natural Language Processing by Denis Rothman, Antonio Gulli |
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4 |
Mastering Transformers by Savaş Yıldırım , Meysam Asgari-Chenaghlu |
|
5 |
Advanced Natural Language Processing with TensorFlow 2 by Ashish Bansal |
|
6 |
Python Natural Language Processing Cookbook By Zhenya Antić |
|
7 |
Getting Started with Google BERT By Sudharsan Ravichandiran |
|
8 |
Exploring GPT-3 By Steve Tingiris |
|
9 |
Applied Natural Language Processing in the Enterprise by Ankur A. Patel, Ajay Uppili Arasanipalai |
|
10 |
Natural Language Processing in Action, Second Edition by Hobson Lane and Maria Dyshel |
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Articles
Sr.No |
Article Name |
Link |
1 |
Computer Vision: Algorithms and Applications |
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2 |
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3 |
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4 |
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5 |
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6 |
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7 |
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8 |
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9 |
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10 |
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Video
Sr.No |
Video Name |
Link |
1 |
Natural Language Processing (University of Michigan) |
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2 |
Stanford CS224N NLP with Deep Learning |
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3 |
Chatbot by Binod Suman Academy |
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4 |
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5 |
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6 |
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7 |
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8 |
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9 |
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10 |
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Extra Resources
Sr.No |
Resource Name |
Link |
1 |
Designing an ML Minded Product |
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2 |
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3 |
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4 |
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5 |
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Credit : ML-ops.org
Books
Sr.No |
Book Name |
Link |
1 |
Engineering MLOps: By Emmanuel Raj |
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2 |
Machine Learning Design Patterns Book by Michael Munn, Sara Robinson, and Valliappa Lakshmanan |
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3 |
Designing Machine Learning Systems Book by Chip Huyen |
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4 |
Practical MLOps by Noah Gift, Alfredo Deza |
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5 |
MLOps Engineering at Scale Book by Carl Osipov |
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6 |
Machine Learning on Kubernetes by Faisal Masood, Ross Brigoli |
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7 |
Machine Learning Engineering with MLflow By Natu Lauchande |
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8 |
Machine Learning Engineering with Python By Andrew P. McMahon |
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9 |
Kubeflow for Machine Learning by Trevor Grant, Holden Karau, Boris Lublinsky, Richard Liu, Ilan Filonenko |
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10. |
Production-Ready Applied Deep Learning By Tomasz Palczewski , Jaejun (Brandon) Lee , Lenin Mookiah |
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Articles
Sr.No |
Article Name |
Link |
1 |
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2 |
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3 |
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4 |
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5 |
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6 |
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7 |
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8 |
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9 |
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10 |
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Video
Sr.No |
Video Name |
Link |
1 |
MLOps Zoomcamp |
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2 |
Machine Learning Engineering for Production (MLOps) Specialization by Andrew Ng |
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3 |
Docker Tutorial in Hindi 2022 |
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4 |
CS 329S: Machine Learning Systems Design |
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5 |
Full Stack Deep Learning 2019 |
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6 |
MLOps - Machine Learning Operations |
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7 |
MLOps: ML Deployment 2020 |
|
8 |
Mlops Live Webinar |
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9 |
Azure MLops |
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10 |
MLOps by Pragmatic AI Labs |
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11 |
MLops Tutorial by DVC.org |
|
12 |
Kubernetes Tutorial for Beginners [FULL COURSE in 4 Hours] |
|
13 |
Docker Tutorials For Beginner - 2 Million view |
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Extra Resources
Sr.No |
Resource Name |
Link |
1 |
Awesome MLops |
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2 |
MadewithML |
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3 |
Awesome Production Machine learning |
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4 |
MLOps - Best Blog(Neptune.ai) |
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5 |
OPERATIONALIZING MACHINE LEARNING |
|
6 |
Practical Guide of MLOps by Google |
|
7 |
Awesome MLOps Guide Tools |
|
8 |
MLops Blogs by MLOps BootCamp |
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9 |
FedML MLOps Introduction |
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10 |
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11 |
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12 |
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13 |
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🙏 Thanks for Reading 🙏 More is coming stay tune ⛹️♂️