Free Hands-on Demo Session organized by Management Career Institute

Topic: Application of AI in price prediction.

Deliverables:
-Basic of data handling part.
-Introducing to forecasting models.
-Introducing Deep learning based forecast.
-Explaining detailed architecture of the DL model.
-Implementing live on real time dataset.

Duration - 2 hours
Date - Thursday | 29th July
Time - 6.30 PM IST (Evening Slot)
Live Hands-on Session

Get Register Now: https://forms.gle/fkRv6dJnymew6sk6A

Who will be Instructor?
Instructor is Lead of Automation (Data Science & Artificial Intelligence) at Wipro. He has solved 60+ Research use cases, published 45+ Patents (received 23 grants) across various countries. He is also a Member of Advisory council at India ka AI.

Swin Transformer for Object Detection

PAPER:
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

VIDEO:
https://www.youtube.com/watch?v=FQVS_0Bja6o

CODE:
https://github.com/SwinTransformer/Swin-Transformer-Object-Detection

@deeplearning_ai

Hey if you are interested in learning data science, machine learning, deep learning or Big data. You will also get to know how to do career transition to data science field.

In this telegram group, you will get daily practice quizzes on interview questions, study materials, cheatsheets, blogs, books for free.

Here is the telegram group that you can join

https://t.me/dataspoof

Top Universities Offering Free Online Programming Courses


https://www.naukri.com/learning/articles/top-universities-offering-free-online-courses-for-programmers/



@deeplearning_ai

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Lane Detection With OpenCV (Part 1)

1. Intro
2. Thresholding
3. Perspective Correction
4. Warping

https://dzone.com/articles/lane-detection-with-opencv


@MachineLearning_Programming

MoveNet : Pose Estimation for Video with Intense Motion

@deeplearning_ai

An important collection of the 15 best machine learning cheat sheets.

مجموعة مهمة الافضل ١٥ ورقة غش في مجال التعلم الآلي.

1- Supervised Learning

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-supervised-learning.pdf

2- Unsupervised Learning

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-unsupervised-learning.pdf

3- Deep Learning

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-deep-learning.pdf

4- Machine Learning Tips and Tricks

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-machine-learning-tips-and-tricks.pdf

5- Probabilities and Statistics

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-probabilities-statistics.pdf

6- Comprehensive Stanford Master Cheat Sheet

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/super-cheatsheet-machine-learning.pdf

7- Linear Algebra and Calculus

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-algebra-calculus.pdf

8- Data Science Cheat Sheet

https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf

9- Keras Cheat Sheet

https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Keras_Cheat_Sheet_Python.pdf

10- Deep Learning with Keras Cheat Sheet

https://github.com/rstudio/cheatsheets/raw/master/keras.pdf

11- Visual Guide to Neural Network Infrastructures

http://www.asimovinstitute.org/wp-content/uploads/2016/09/neuralnetworks.png

12- Skicit-Learn Python Cheat Sheet

https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf

13- Scikit-learn Cheat Sheet: Choosing the Right Estimator

https://scikit-learn.org/stable/tutorial/machine_learning_map/

14- Tensorflow Cheat Sheet

https://github.com/kailashahirwar/cheatsheets-ai/blob/master/PDFs/Tensorflow.pdf

15- Machine Learning Test Cheat Sheet

https://www.cheatography.com/lulu-0012/cheat-sheets/test-ml/pdf/

@deeplearning_ai