Day 30 resources
1. https://www.youtube.com/watch?v=Q81RR3yKn30
2. https://www.youtube.com/watch?v=NGf0voTMlcs
3. https://towardsdatascience.com/intuitions-on-l1-and-l2-regularisation-235f2db4c261
4. http://enhancedatascience.com/2017/07/04/machine-learning-explained-regularization/
5. https://medium.com/datadriveninvestor/l1-l2-regularization-7f1b4fe948f2
6.https://medium.com/datadriveninvestor/l1-l2-regularization-7f1b4fe948f2
7.https://developers.google.com/machine-learning/crash-course/regularization-for-simplicity/l2-regularization
1. https://www.youtube.com/watch?v=Q81RR3yKn30
2. https://www.youtube.com/watch?v=NGf0voTMlcs
3. https://towardsdatascience.com/intuitions-on-l1-and-l2-regularisation-235f2db4c261
4. http://enhancedatascience.com/2017/07/04/machine-learning-explained-regularization/
5. https://medium.com/datadriveninvestor/l1-l2-regularization-7f1b4fe948f2
6.https://medium.com/datadriveninvestor/l1-l2-regularization-7f1b4fe948f2
7.https://developers.google.com/machine-learning/crash-course/regularization-for-simplicity/l2-regularization
2009_Book_TheElementsOfStatisticalLearni.pdf
15.2 MB
The Best book to learn machine learning in depth
Day 31 resources -
1. https://towardsdatascience.com/understanding-logistic-regression-9b02c2aec102
2. https://www.youtube.com/watch?v=yIYKR4sgzI8
3. https://www.youtube.com/watch?v=vN5cNN2-HWE
4. https://www.youtube.com/watch?v=BfKanl1aSG0
5. https://www.youtube.com/watch?v=xxFYro8QuXA
6. https://www.datacamp.com/community/tutorials/understanding-logistic-regression-python
1. https://towardsdatascience.com/understanding-logistic-regression-9b02c2aec102
2. https://www.youtube.com/watch?v=yIYKR4sgzI8
3. https://www.youtube.com/watch?v=vN5cNN2-HWE
4. https://www.youtube.com/watch?v=BfKanl1aSG0
5. https://www.youtube.com/watch?v=xxFYro8QuXA
6. https://www.datacamp.com/community/tutorials/understanding-logistic-regression-python
List of Awesome Open Source Machine Learning Repos
https://towardsdatascience.com/list-of-awesome-open-source-machine-learning-repos-537fdc08ad4d
https://towardsdatascience.com/list-of-awesome-open-source-machine-learning-repos-537fdc08ad4d
Medium
List of Awesome Open Source Machine Learning Project Repos
Try this list of open-source project repositories to make your machine learning experience awesome
IIT Kharagpur Offers Free Online Course on Deep Learning for Engineers through NPTEL
https://www.dqindia.com/iit-kharagpur-offers-free-online-course-deep-learning-engineers-nptel/
https://www.dqindia.com/iit-kharagpur-offers-free-online-course-deep-learning-engineers-nptel/
Day 33 resources -
1. https://www.youtube.com/watch?v=TP9W7hmb0Bs
2. https://www.youtube.com/watch?v=RublDm4J1vY
3. https://towardsdatascience.com/hyperparameter-tuning-explained-d0ebb2ba1d35
4. https://www.jeremyjordan.me/hyperparameter-tuning/
5. https://www.coursera.org/lecture/competitive-data-science/hyperparameter-tuning-i-giBKx
6.https://towardsdatascience.com/automated-machine-learning-hyperparameter-tuning-in-python-dfda59b72f8a
7.https://towardsdatascience.com/hyper-parameter-tuning-techniques-in-deep-learning-4dad592c63c8
1. https://www.youtube.com/watch?v=TP9W7hmb0Bs
2. https://www.youtube.com/watch?v=RublDm4J1vY
3. https://towardsdatascience.com/hyperparameter-tuning-explained-d0ebb2ba1d35
4. https://www.jeremyjordan.me/hyperparameter-tuning/
5. https://www.coursera.org/lecture/competitive-data-science/hyperparameter-tuning-i-giBKx
6.https://towardsdatascience.com/automated-machine-learning-hyperparameter-tuning-in-python-dfda59b72f8a
7.https://towardsdatascience.com/hyper-parameter-tuning-techniques-in-deep-learning-4dad592c63c8
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The latest version of AI App by Nvidia generates a seemingly infinite number of portraits in any painting styles
link - https://news.developer.nvidia.com/synthesizing-high-resolution-images-with-stylegan2/
link - https://news.developer.nvidia.com/synthesizing-high-resolution-images-with-stylegan2/
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Haptik open sourced a NLP toolkit (multi-task-NLP) to help train multiple models in 3 simple steps without the need to code.
1. (Query-passage) Answerability prediction
2. Textual entailment (can be used for question answering, adversarial query detection)
3. Intent detection + Named entity detection + Fragment detection (Multi - task setup)
4. Named entity recognition + part of speech tagging ( Multi-task )
5. Query grammatical correctness
6. Query pair similarity (QnA)
7. Query type detection
8. Sentiment analysis
Github : https://lnkd.in/dGmYzVT
Documentation : https://lnkd.in/duRX4fS
1. (Query-passage) Answerability prediction
2. Textual entailment (can be used for question answering, adversarial query detection)
3. Intent detection + Named entity detection + Fragment detection (Multi - task setup)
4. Named entity recognition + part of speech tagging ( Multi-task )
5. Query grammatical correctness
6. Query pair similarity (QnA)
7. Query type detection
8. Sentiment analysis
Github : https://lnkd.in/dGmYzVT
Documentation : https://lnkd.in/duRX4fS