awesome-deepnote
A curated list of extensions, python packages, machine learning and collaborative notebooks ready to run in Deepnote.
https://github.com/ramene/awesome-deepnote
Last synced: 4 days ago
JSON representation
-
Other Awesome Lists
-
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- lists
- pytudes
- awesome-machine-learning-on-source-code
- awesome-graph-classification
- awesome-decision-tree-papers
- awesome-fraud-detection-papers
- machine-learning-for-software-engineers
- Reviewing Deepnote — The New IDE for Data Scientists
- awesome-r
- awesome-aws
- awesome-python
- awesome-tensorflow
- awesome-datascience
- awesome-machine-learning
- Deepnote: the modern way to teach Data Science
- #awesome - lists](https://github.com/topics/awesome-lists)
- Collaborative notebooks for ML course at Cambridge
- Reviewing Deepnote — The New IDE for Data Scientists
- Deepnote Emerges from Stealth: With YC, Index, and Accel Leading Our Seed Round
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Glossary of common statistics and ML terms
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- awesome-datascience-ideas
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
- awesome-public-datasets
- awesome-dataviz
- Reviewing Deepnote — The New IDE for Data Scientists
- Reviewing Deepnote — The New IDE for Data Scientists
-
License
-
-
General
- Visual data exploration with Virginia's public COVID-19 cases dataset - bot)
- Datascience IPython Notebooks
- Maths: Form and Function with Python - G-Hill)
- Using Conda in Deepnote in 3 simple steps
- Tensorboard with ngrok
- Scraping the EPL Stats Website
- Intro to Deep Learning
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - e-thomas/deeptnote-credit-card-fraud)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img alt="by Peter Norvig" height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub>
- <sub><sub><img alt="by Peter Norvig" height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - Programming-and-Bayesian-Methods-for-Hackers)
- <sub><sub><img alt="by Peter Norvig" height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - for-Probability-Statistics-and-Machine-Learning-2E)
- <sub><sub><img alt="by Peter Norvig" height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - the-Social-Web-3rd-Edition/tree/master/notebooks) by [Mikhail Klassen](https://github.com/mikhailklassen)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - e-thomas/deeptnote-credit-card-fraud)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - e-thomas/deeptnote-credit-card-fraud)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
- Maths: Form and Function with Python - G-Hill)
- <sub><sub><img height="20" src="https://deepnote.com/buttons/launch-in-deepnote.svg"></sub></sub> - churn-prediction/blob/master/notebooks/customer-churn-prediction.ipynb)
-
Integrations
-
Resources
Programming Languages
Sub Categories
Keywords
machine-learning
6
awesome-list
5
python
4
awesome
4
data-science
4
deep-learning
4
data-mining
2
classifier
2
gradient-boosting
2
aws
2
graph-classification
2
data-visualization
2
random-forest
2
graph-convolutional-networks
1
graph-embedding
1
graph-kernel
1
graph-kernels
1
graph-attention-networks
1
graph-attention-model
1
deepwalk
1
deep-graph-kernels
1
classification-algorithm
1
attention-mechanism
1
machine-learning-on-source-code
1
graph-representation-learning
1
graph2vec
1
kernel-methods
1
netlsd
1
network-embedding
1
node-embedding
1
node2vec
1
structural-attention
1
weisfeiler-lehman
1
cart
1
catboost
1
classification-model
1
classification-trees
1
decision-tree
1
covid-19
1
datapane
1
deepnote
1
plotly
1
population
1
virginia
1
big-data
1
caffe
1
hadoop
1
kaggle
1
keras
1
mapreduce
1