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This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.
| Date | Stars |
|---|---|
| 2026-07-24 | 396 |
| 2026-07-25 | 396 |
| 2026-07-28 | 396 |
| 2026-07-30 | 396 |
| 2026-08-06 | 396 |
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<H3>The Semicolon</H3> This repository contains the Ipython Notebooks to the Data Analytics youtube tutorials on The Semicolon. The youtube link for the tutorials :https://www.youtube.com/c/thesemicolon The following Ipython notebooks are available on this repository. Python for Data Analytics <br /> 1. [Learn Python in 10 Minutes](../master/Python%202.7%20Basics.ipynb) <br /> 2. [Numpy and Matplotlib Tutorial](../master/Numpy%20and%20matplotlib.ipynb) <br /> 3. [Pandas tutorial](../master/Pandas%20Tutorial.ipynb) <br /> 4. [Sklearn linear regression](../master/Sklearn%20Tutorial%20-%20Housing%20example.ipynb) <br /> 5. [Sklearn Random Forest Classifier](../master/Handwriting%20Recognition.ipynb) <br /> 6. [Sklearn dimensionality reduction](../master/Dim.%20Reduction.ipynb) <br/> 6. [Machine Learning with Text Count Vectorizer](../master/Text%20Analytics%20CV.ipynb)<br /> 7. [Machine Learning with Text TF- IDF](../master/Text%20Analytics%20tfidf.ipynb) <br /> 8. [Live Sentiment Analysis](../master/livesenti.py) <br /> 9. [Perceptron And Gradient Descent](../master/Perceptron%20and%20Gradient%20Descent.ipynb)<br/> 10. [Neural Networks and Backpropogation Algorithm](../master/Neural%20Networks%20and%20BackPropogation.ipynb) <br/> 11. [Ensemble Learning](../master/Ensemble%20Learning.ipynb) <br/> Deep Learning with Keras <br /> 1. [Convolutional Neural Networks with Keras](../master/cnn.py) <br/> 2. [Word2vec implementation in gensim](../master/word2vec.py) <br/> 3. [Simple LSTM implementation with Keras](../master/lstm%20-%20RNN.py) <br /> 4. [LSTM implementation details with Keras, Normailzation, Activation, Loss](../master/lstmaccuracy.py) <br /> 5. [Chatbot Preprocessing](../master/chatbotPreprocessing.py) <br/> 6. [Chatbot training](../master/chatbotlstmtrain.py) <br/> 7. [Chatbot Chat](../master/chat.py) <br/> 8. Chatbot Trained models: https://drive.google.com/drive/folders/0B2P-tOw32QIWZnYyY3J3OVNLYzg <br> <br> Apart from this the datasets used are housing.csv, mnist.csv and smsspam
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:971ebf457c7fb9e3, topic:deep-learning, topic:neural-network
matched fp:971ebf457c7fb9e3, topic:sentiment-analysis, readme:sentiment analysis
matched fp:971ebf457c7fb9e3, topic:tutorial, readme:tutorial