Deep Learning Do It Yourself!
This site collects resources to learn Deep Learning in the form of Modules available through the sidebar on the left.
https://dataflowr.github.io/website/
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This site collects resources to learn Deep Learning in the form of Modules available through the sidebar on the left.
https://dataflowr.github.io/website/
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Join @datascience_bds for more cool data science materials.
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Forwarded from Coding interview preparation
🔗 Book link
#machinelearning #ml #datascience
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*This channel belongs to @bigdataspecialist group
#machinelearning #ml #datascience
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Lectures for UC Berkeley CS 182: Deep Learning
Spring 2021
🎬 66 videos
⏰ 26 hours
https://www.youtube.com/playlist?list=PL_iWQOsE6TfVmKkQHucjPAoRtIJYt8a5A
#deeplearning
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Spring 2021
🎬 66 videos
⏰ 26 hours
https://www.youtube.com/playlist?list=PL_iWQOsE6TfVmKkQHucjPAoRtIJYt8a5A
#deeplearning
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YouTube
Deep Learning: CS 182 Spring 2021
Lectures for UC Berkeley CS 182: Deep Learning.
The Incredible PyTorch
A curated list of tutorials, papers, projects, communities and more relating to PyTorch.
https://www.ritchieng.com/the-incredible-pytorch/
#pytorch
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*This channel belongs to @bigdataspecialist group
A curated list of tutorials, papers, projects, communities and more relating to PyTorch.
https://www.ritchieng.com/the-incredible-pytorch/
#pytorch
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*This channel belongs to @bigdataspecialist group
FOUNDATIONS OF MACHINE LEARNING
by Bloomberg
Understand the Concepts, Techniques and Mathematical Frameworks Used by Experts in Machine Learning
🎬 30 video lessons with slides
⏰ 28 hours
https://bloomberg.github.io/foml/#home
#machinelearning #ml
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*This channel belongs to @bigdataspecialist group
by Bloomberg
Understand the Concepts, Techniques and Mathematical Frameworks Used by Experts in Machine Learning
🎬 30 video lessons with slides
⏰ 28 hours
https://bloomberg.github.io/foml/#home
#machinelearning #ml
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*This channel belongs to @bigdataspecialist group
Intro to Machine Learning
by Kaggle
Learn the core ideas in machine learning, and build your first models.
1 How Models Work
The first step if you're new to machine learning.
2 Basic Data Exploration
Load and understand your data.
3 Your First Machine Learning Model
Building your first model. Hurray!
4 Model Validation
Measure the performance of your model, so you can test and compare alternatives.
5 Underfitting and Overfitting
Fine-tune your model for better performance.
6 Random Forests
Using a more sophisticated machine learning algorithm.
7 Machine Learning Competitions
Enter the world of machine learning competitions to keep improving and see your progress.
🔗 Course link
#machinelearning #ml
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*This channel belongs to @bigdataspecialist group
by Kaggle
Learn the core ideas in machine learning, and build your first models.
1 How Models Work
The first step if you're new to machine learning.
2 Basic Data Exploration
Load and understand your data.
3 Your First Machine Learning Model
Building your first model. Hurray!
4 Model Validation
Measure the performance of your model, so you can test and compare alternatives.
5 Underfitting and Overfitting
Fine-tune your model for better performance.
6 Random Forests
Using a more sophisticated machine learning algorithm.
7 Machine Learning Competitions
Enter the world of machine learning competitions to keep improving and see your progress.
🔗 Course link
#machinelearning #ml
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*This channel belongs to @bigdataspecialist group
Kaggle
Learn Intro to Machine Learning Tutorials
Learn the core ideas in machine learning, and build your first models.
Reproducible Data Science with Docker
https://archive.org/details/pyconza2018-Reproducible_Data_Science_with_Docker
https://archive.org/details/pyconza2018-Reproducible_Data_Science_with_Docker
Internet Archive
Reproducible Data Science with Docker : Richard Ackon : Free Download, Borrow, and Streaming : Internet Archive
Richard Ackon https://2018.za.pycon.org/talks/48-reproducible-data-science-with-docker/ Collaboration is a major part of doing Data Science. This means Data...
The R Programming For Data Science A-Z Complete Diploma 2022
Rating ⭐️: 4.5 out of 5
Students 👨🎓: 38,584
Duration ⏰: 5h 6min
🔗 Course link
Free for first 1000 enrollments
Rating ⭐️: 4.5 out of 5
Students 👨🎓: 38,584
Duration ⏰: 5h 6min
🔗 Course link
Free for first 1000 enrollments
Udemy
Data Science: R Programming Complete Diploma 2023
Learn all the R skills you need to become a Professional and Certified R Programmer with this Complete Bootcamp
Forwarded from Free programming books
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Knowledge Graphs Course
Data Models, Knowledge Acquisition, Inference and Applications
Department of Computer Science, Stanford University, Spring 2021
⏳10 weeks, each week has slides and video lessons 📽
https://web.stanford.edu/class/cs520/
#datascience #machinelearning #tensorflow #scikitlearn #keras
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Data Models, Knowledge Acquisition, Inference and Applications
Department of Computer Science, Stanford University, Spring 2021
⏳10 weeks, each week has slides and video lessons 📽
https://web.stanford.edu/class/cs520/
#datascience #machinelearning #tensorflow #scikitlearn #keras
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Join @programming_books_bds for more