ChargeZoneApr2023
AI-For-Beginners
ChargeZoneApr2023 | AI-For-Beginners | |
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2 | 8 | |
3 | 32,359 | |
- | 4.1% | |
6.7 | 7.4 | |
almost 1 year ago | 3 days ago | |
Jupyter Notebook | Jupyter Notebook | |
GNU General Public License v3.0 or later | MIT License |
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ChargeZoneApr2023
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Is the EV Charging business profitable?
Link to code - https://github.com/jnerurkar/ChargeZoneApr2023
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ChargeZone Insights - April 2023
Article Link - https://expwithevs.substack.com/p/chargezone-insights-for-april-2023 Data link - https://docs.google.com/spreadsheets/d/1psvAQ8_ba2GI4V_rCyDAz8OzwxloWWbcuxGmyWcw3lk/edit#gid=0 Code link - https://github.com/jnerurkar/ChargeZoneApr2023
AI-For-Beginners
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FREE AI Course By Microsoft: ZERO to HERO! 🔥
🔗 https://github.com/microsoft/AI-For-Beginners 🔗 https://microsoft.github.io/AI-For-Beginners/
- AI For Beginners
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Artificial Intelligence for Beginners – A Curriculum
This is a good summary of most topics in AI/ML. The only thing that it seems to by missing (or maybe I'm just not seeing it) is a section on generative AI for images and video (DALL-E, Stable Diffusion etc).
They do cover LLMs which is generative AI for text though: https://github.com/microsoft/AI-For-Beginners/blob/main/less...
- Artificial Intelligence course
- Artificial Intelligence for Beginners course
- Microsoft's AI for Beginners
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Announcing a New Free Curriculum: Artificial Intelligence for Beginners
Students can use this curriculum to learn the basics of AI and Neural Networks. In addition to text-based lessons, there are executable Jupyter Notebooks with samples, as well as labs that you can do to deepen your knowledge. You can run notebooks either on your local computer or in the cloud. Join your peers on GitHub Discussion Boards to learn together and watch for more learning opportunities online.
What are some alternatives?
open_clip - An open source implementation of CLIP.
GAN-RNN_Timeseries-imputation - Recurrent GAN for imputation of time series data. Implemented in TensorFlow 2 on Wikipedia Web Traffic Forecast dataset from Kaggle.
DeepLearning - Contains all my works, references for deep learning
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
Twitter-sentiment-analysis - A sentiment analysis model trained with Kaggle GPU on 1.6M examples, used to make inferences on 220k tweets about Messi and draw insights from their results.
CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.
conformal_classification - Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).
TSAI-DeepNLP-END2.0
LLVIP - LLVIP: A Visible-infrared Paired Dataset for Low-light Vision
CAH - Code used for Cards Against Humanity EMNLP paper
Artifact_Removal_GAN - A U-net GAN for jpeg artifact removal
xformers - Hackable and optimized Transformers building blocks, supporting a composable construction.