Goodreads-Review-Webscraping-and-Text-Analysis
AI-For-Beginners
| Goodreads-Review-Webscraping-and-Text-Analysis | AI-For-Beginners | |
|---|---|---|
| 1 | 8 | |
| 0 | 31,481 | |
| - | 3.7% | |
| 6.9 | 6.7 | |
| 12 months ago | 25 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | MIT License |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Goodreads-Review-Webscraping-and-Text-Analysis
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Need help with GitHub scraping project in Google colab
So I have to write a paper for a literary course, in which I need to analyse Goodreads reviews of a book (Bewilderment by Richard Powers). The professor told me to search GitHub for “goodreads reviews scraping colab” with Jupyter notebook but unless I leave “colab” out of the query, there are no repositories showing (I'm not even sure it needs to be a repository, or simply just code). He told me to look for the newest, which I believe is this one. The next step is to use it in “Google colab“ but I have no idea what that is or how to access it. I‘d really appreciate your help! Thanks.
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?
ML-Papers-of-the-Week - 🔥Highlighting the top ML papers every week.
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
Basic-number-captcha-solver - This repo is for solving captcha images on METU student portal's course capacity check section.