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π Model: https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0
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π Model: https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0
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Please more 100 π with our posts
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π¨π»βπ» Data science researcher Keith McNulty has published the complete content of the R for People Analytics course online for free . The content of this course includes:
1) All textbooks + slides during the course
2) Interactive exercises using RStudio Cloud
3) Course project datasets
β π· RStudio conf 2022
β π R for People Analytics
This course contains resources that mainly focus on R. For a deeper understanding of working with R for data analysts, McNulty has made two of his textbooks free :
β π· Two FREE online textbooks R
β π Regression Modeling with R
β π Graphs & Networks with R
https://t.me/CodeProgrammer
1) All textbooks + slides during the course
2) Interactive exercises using RStudio Cloud
3) Course project datasets
β π· RStudio conf 2022
β π R for People Analytics
This course contains resources that mainly focus on R. For a deeper understanding of working with R for data analysts, McNulty has made two of his textbooks free :
β π· Two FREE online textbooks R
β π Regression Modeling with R
β π Graphs & Networks with R
https://t.me/CodeProgrammer
+160 Data Science Projects You Can Try with Python
+160 Data Science Projects solved & explained with Python
β π· Data Science Projects with Python
β π +160 Data Science Projects
β https://t.me/CodeProgrammer
+160 Data Science Projects solved & explained with Python
β π· Data Science Projects with Python
β π +160 Data Science Projects
β https://t.me/CodeProgrammer
π€ Machine Learning Tutorials Repository
1. Python
2. Computer Vision: Techniques, algorithms
3. NLP
4. Matplotlib
5. NumPy
6. Pandas
7. MLOps
8. LLMs
9. PyTorch/TensorFlow
π GitHub: https://github.com/patchy631/machine-learning/tree/main
βοΈ https://t.me/DataScienceT
1. Python
2. Computer Vision: Techniques, algorithms
3. NLP
4. Matplotlib
5. NumPy
6. Pandas
7. MLOps
8. LLMs
9. PyTorch/TensorFlow
git clone https://github.com/patchy631/machine-learning
π GitHub: https://github.com/patchy631/machine-learning/tree/main
βοΈ https://t.me/DataScienceT
β
The best sources for downloading datasets for free
β π· Real world data
β βΌοΈ Data.gov
β β»οΈ Kaggle
β βΌοΈ Dataset Search
β β»οΈ DataHub
β βΌοΈ Earth Data
β β»οΈ WHO data repository
βοΈ https://t.me/CodeProgrammer
β π· Real world data
β βΌοΈ Data.gov
β β»οΈ Kaggle
β βΌοΈ Dataset Search
β β»οΈ DataHub
β βΌοΈ Earth Data
β β»οΈ WHO data repository
βοΈ https://t.me/CodeProgrammer
βοΈ IBM Free course: Python Basics for Data Science
Course Link: https://www.edx.org/learn/python/ibm-python-basics-for-data-science
βοΈ https://t.me/CodeProgrammer
Course Link: https://www.edx.org/learn/python/ibm-python-basics-for-data-science
βοΈ https://t.me/CodeProgrammer
π₯ Extracting Tables from a PDF
Code: https://github.com/jsvine/pdfplumber
βοΈ https://t.me/CodeProgrammer
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Code: https://github.com/jsvine/pdfplumber
βοΈ https://t.me/CodeProgrammer
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π΄π’We sincerely invite you to join our DeFi smart mining team:
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A mobile phone and an encrypted wallet are all you need to start earning money from mining.
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πWe are committed to providing every enthusiastic investor with accurate investment strategies and market analysis, with an average daily income of 100-500 USDT.
Join the DeFi Smart Mining Telegram channel: https://t.me/DeFimobilemining
View more information about mining activities.π°Invite friends to join and you can get 10% of the friendsβ income and 10% of the income of the friends introduced by your friendsπ°
Free Datasets to practice data science projects
1. Enron Email Dataset
Data Link: https://www.cs.cmu.edu/~enron/
2. Chatbot Intents Dataset
Data Link: https://github.com/katanaml/katana-assistant/blob/master/mlbackend/intents.json
3. Flickr 30k Dataset
Data Link: https://www.kaggle.com/hsankesara/flickr-image-dataset
4. Parkinson Dataset
Data Link: https://archive.ics.uci.edu/ml/datasets/parkinsons
5. Iris Dataset
Data Link: https://archive.ics.uci.edu/ml/datasets/Iris
6. ImageNet dataset
Data Link: http://www.image-net.org/
7. Mall Customers Dataset
Data Link: https://www.kaggle.com/shwetabh123/mall-customers
8. Google Trends Data Portal
Data Link: https://trends.google.com/trends/
9. The Boston Housing Dataset
Data Link: https://www.cs.toronto.edu/~delve/data/boston/bostonDetail.html
10. Uber Pickups Dataset
Data Link: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city
11. Recommender Systems Dataset
Data Link: https://cseweb.ucsd.edu/~jmcauley/datasets.html
Source Code: https://bit.ly/37iBDEp
12. UCI Spambase Dataset
Data Link: https://archive.ics.uci.edu/ml/datasets/Spambase
13. GTSRB (German traffic sign recognition benchmark) Dataset
Data Link: http://benchmark.ini.rub.de/?section=gtsrb&subsection=dataset
Source Code: https://bit.ly/39taSyH
14. Cityscapes Dataset
Data Link: https://www.cityscapes-dataset.com/
15. Kinetics Dataset
Data Link: https://deepmind.com/research/open-source/kinetics
16. IMDB-Wiki dataset
Data Link: https://data.vision.ee.ethz.ch/cvl/rrothe/imdb-wiki/
17. Color Detection Dataset
Data Link: https://github.com/codebrainz/color-names/blob/master/output/colors.csv
18. Urban Sound 8K dataset
Data Link: https://urbansounddataset.weebly.com/urbansound8k.html
19. Librispeech Dataset
Data Link: http://www.openslr.org/12
20. Breast Histopathology Images Dataset
Data Link: https://www.kaggle.com/paultimothymooney/breast-histopathology-images
21. Youtube 8M Dataset
Data Link: https://research.google.com/youtube8m/
βοΈ https://t.me/CodeProgrammer
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1. Enron Email Dataset
Data Link: https://www.cs.cmu.edu/~enron/
2. Chatbot Intents Dataset
Data Link: https://github.com/katanaml/katana-assistant/blob/master/mlbackend/intents.json
3. Flickr 30k Dataset
Data Link: https://www.kaggle.com/hsankesara/flickr-image-dataset
4. Parkinson Dataset
Data Link: https://archive.ics.uci.edu/ml/datasets/parkinsons
5. Iris Dataset
Data Link: https://archive.ics.uci.edu/ml/datasets/Iris
6. ImageNet dataset
Data Link: http://www.image-net.org/
7. Mall Customers Dataset
Data Link: https://www.kaggle.com/shwetabh123/mall-customers
8. Google Trends Data Portal
Data Link: https://trends.google.com/trends/
9. The Boston Housing Dataset
Data Link: https://www.cs.toronto.edu/~delve/data/boston/bostonDetail.html
10. Uber Pickups Dataset
Data Link: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city
11. Recommender Systems Dataset
Data Link: https://cseweb.ucsd.edu/~jmcauley/datasets.html
Source Code: https://bit.ly/37iBDEp
12. UCI Spambase Dataset
Data Link: https://archive.ics.uci.edu/ml/datasets/Spambase
13. GTSRB (German traffic sign recognition benchmark) Dataset
Data Link: http://benchmark.ini.rub.de/?section=gtsrb&subsection=dataset
Source Code: https://bit.ly/39taSyH
14. Cityscapes Dataset
Data Link: https://www.cityscapes-dataset.com/
15. Kinetics Dataset
Data Link: https://deepmind.com/research/open-source/kinetics
16. IMDB-Wiki dataset
Data Link: https://data.vision.ee.ethz.ch/cvl/rrothe/imdb-wiki/
17. Color Detection Dataset
Data Link: https://github.com/codebrainz/color-names/blob/master/output/colors.csv
18. Urban Sound 8K dataset
Data Link: https://urbansounddataset.weebly.com/urbansound8k.html
19. Librispeech Dataset
Data Link: http://www.openslr.org/12
20. Breast Histopathology Images Dataset
Data Link: https://www.kaggle.com/paultimothymooney/breast-histopathology-images
21. Youtube 8M Dataset
Data Link: https://research.google.com/youtube8m/
βοΈ https://t.me/CodeProgrammer
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Computers are getting better than humans in classifying objects π³π―
With Computer Vision will AI take over the planet Earth? π€·π»ββοΈπ¨
Here is a pack of 5 resources about the upcoming field - Computer Vision
What is Computer Vision?
https://data-flair.training/blogs/ai-python-computer-vision/
Computer Vision Projects
https://data-flair.training/blogs/computer-vision-project-ideas/
Road Lane line detection β Computer Vision Project in Python
https://data-flair.training/blogs/road-lane-line-detection/
Real-time Human Detection & Counting β Computer Vision Project in Python
https://data-flair.training/blogs/python-project-real-time-human-detection-counting/
Driver Drowsiness Detection β Computer Vision Project in Python
https://data-flair.training/blogs/python-project-driver-drowsiness-detection-system/
βοΈ https://t.me/CodeProgrammer
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With Computer Vision will AI take over the planet Earth? π€·π»ββοΈπ¨
Here is a pack of 5 resources about the upcoming field - Computer Vision
What is Computer Vision?
https://data-flair.training/blogs/ai-python-computer-vision/
Computer Vision Projects
https://data-flair.training/blogs/computer-vision-project-ideas/
Road Lane line detection β Computer Vision Project in Python
https://data-flair.training/blogs/road-lane-line-detection/
Real-time Human Detection & Counting β Computer Vision Project in Python
https://data-flair.training/blogs/python-project-real-time-human-detection-counting/
Driver Drowsiness Detection β Computer Vision Project in Python
https://data-flair.training/blogs/python-project-driver-drowsiness-detection-system/
βοΈ https://t.me/CodeProgrammer
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Programming for everybody (getting started with python)
Free course from coursera:
https://www.coursera.org/learn/python
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Free course from coursera:
https://www.coursera.org/learn/python
βοΈ https://t.me/CodeProgrammer
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Forwarded from Eng. Hussein Sheikho π¨βπ»
This channels is for Programmers, Coders, Software Engineers.
0- Python
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
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6- Statistics
7- Deep Learning
8- programming Languages
β https://t.me/addlist/8_rRW2scgfRhOTc0
β https://t.me/DataScienceM
0- Python
1- Data Science
2- Machine Learning
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4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
8- programming Languages
β https://t.me/addlist/8_rRW2scgfRhOTc0
β https://t.me/DataScienceM
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π₯ Harvard's popular CS50 series has an intro to Python course taught by David J. Malan himself.
Harvard's popular CS50 course series includes an Introduction to Python course taught by David Jay Malan himself.
The course covers Python fundamentals such as loops and conditions, and writing and using APIs.
Along the way, you'll build an application using frameworks such as Django and React.
Course: https://cs50.harvard.edu/python/2022/
Videos: https://www.youtube.com/watch?v=nLRL_NcnK-4
π https://t.me/CodeProgrammer
More Likes, Share, Subscribe πβ€οΈ
Harvard's popular CS50 course series includes an Introduction to Python course taught by David Jay Malan himself.
The course covers Python fundamentals such as loops and conditions, and writing and using APIs.
Along the way, you'll build an application using frameworks such as Django and React.
Course: https://cs50.harvard.edu/python/2022/
Videos: https://www.youtube.com/watch?v=nLRL_NcnK-4
π https://t.me/CodeProgrammer
More Likes, Share, Subscribe πβ€οΈ
CS25: Transformers United V3
New lectures on the course on Transformers from Stanford! Stanford CS 25 " Transformers United " featured celebrity guests such as Andriy Karpaty, Noam Brown, Lukas Beyer and Geoff Hinton himself!
A new report has been released on the creation and recipes for creating universal AI agents in open worlds:
π’ MineDojo : an open framework and multimodal database for training Minecraft agents.
π’ Voyager : agent for lifelong learning in Minecraft based on LLM.
π’ Eureka: GPT-4 develops reward functions to teach a robot hand to turn a knob.
π’ VIMA : one of the earliest multimodal LLMs.
π’A look into the future: promising areas of research.
βοΈ Slides : https://drive.google.com/file/d/1lWIhijUaTZkkWOC_YwZHMoI0h7EAWVPL/view
π Lectures : https://web.stanford.edu/class/cs25
π https://t.me/CodeProgrammer
More Likes, Share, Subscribe πβ€οΈ
New lectures on the course on Transformers from Stanford! Stanford CS 25 " Transformers United " featured celebrity guests such as Andriy Karpaty, Noam Brown, Lukas Beyer and Geoff Hinton himself!
A new report has been released on the creation and recipes for creating universal AI agents in open worlds:
π’ MineDojo : an open framework and multimodal database for training Minecraft agents.
π’ Voyager : agent for lifelong learning in Minecraft based on LLM.
π’ Eureka: GPT-4 develops reward functions to teach a robot hand to turn a knob.
π’ VIMA : one of the earliest multimodal LLMs.
π’A look into the future: promising areas of research.
βοΈ Slides : https://drive.google.com/file/d/1lWIhijUaTZkkWOC_YwZHMoI0h7EAWVPL/view
π Lectures : https://web.stanford.edu/class/cs25
π https://t.me/CodeProgrammer
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