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π₯ Trending Repository: ML-From-Scratch
π Description: Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
π Repository URL: https://github.com/eriklindernoren/ML-From-Scratch
π Readme: https://github.com/eriklindernoren/ML-From-Scratch#readme
π Statistics:
π Stars: 27.8K stars
π Watchers: 951
π΄ Forks: 4.8K forks
π» Programming Languages: Python
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π§ By: https://xn--r1a.website/DataScienceM
π Description: Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
π Repository URL: https://github.com/eriklindernoren/ML-From-Scratch
π Readme: https://github.com/eriklindernoren/ML-From-Scratch#readme
π Statistics:
π Stars: 27.8K stars
π Watchers: 951
π΄ Forks: 4.8K forks
π» Programming Languages: Python
π·οΈ Related Topics:
#data_science #machine_learning #data_mining #deep_learning #genetic_algorithm #deep_reinforcement_learning #machine_learning_from_scratch
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π§ By: https://xn--r1a.website/DataScienceM
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π₯ Trending Repository: Data-Science-For-Beginners
π Description: 10 Weeks, 20 Lessons, Data Science for All!
π Repository URL: https://github.com/microsoft/Data-Science-For-Beginners
π Readme: https://github.com/microsoft/Data-Science-For-Beginners#readme
π Statistics:
π Stars: 31.9K stars
π Watchers: 513
π΄ Forks: 6.8K forks
π» Programming Languages: Jupyter Notebook
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π§ By: https://xn--r1a.website/DataScienceM
π Description: 10 Weeks, 20 Lessons, Data Science for All!
π Repository URL: https://github.com/microsoft/Data-Science-For-Beginners
π Readme: https://github.com/microsoft/Data-Science-For-Beginners#readme
π Statistics:
π Stars: 31.9K stars
π Watchers: 513
π΄ Forks: 6.8K forks
π» Programming Languages: Jupyter Notebook
π·οΈ Related Topics:
#python #data_science #pandas #data_visualization #data_analysis #microsoft_for_beginners
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π¨π»βπ» When I was just starting out and trying to get into the "data" field, I had no one to guide me, nor did I know what exactly I should study. To be honest, I was confused for months and felt lost.
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π Deep Learning for Images with PyTorch: CNNs to GANs
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π Course Details:
This advanced computer vision course delivers a hands-on exploration of PyTorch across all major vision tasks. From Convolutional Neural Networks (CNNs) for image classification to advanced segmentation masks and Generative Adversarial Networks (GANs), it prepares practitioners for complex computer vision engineering tasks.
Who It's For
Advanced PyTorch practitioners, computer vision engineers, and machine learning research engineers seeking deep technical expertise in image processing and synthesis.
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β’ CNNs & Object Detection: Train CNNs for binary and multi-class classification, leverage pre-trained models, and evaluate object detection using bounding boxes.
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#Data_Science
#DataCamp
π« Platform: DataCamp
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π Course Details:
This advanced computer vision course delivers a hands-on exploration of PyTorch across all major vision tasks. From Convolutional Neural Networks (CNNs) for image classification to advanced segmentation masks and Generative Adversarial Networks (GANs), it prepares practitioners for complex computer vision engineering tasks.
Who It's For
Advanced PyTorch practitioners, computer vision engineers, and machine learning research engineers seeking deep technical expertise in image processing and synthesis.
Key Takeaways
β’ CNNs & Object Detection: Train CNNs for binary and multi-class classification, leverage pre-trained models, and evaluate object detection using bounding boxes.
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π’ Channel: https://xn--r1a.website/Courses27
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