https://github.com/ksharma67/ibm-stock-predication-wiith-eda

In this i tried to design a model that can predict the price of stock using different methods and algorithms.
https://github.com/ksharma67/ibm-stock-predication-wiith-eda

bullish-signal death-cross decision-tree eda golden-cross gradient-boosting knn machine-learning-algorithms matplotlib numpy pandas prediction python random-forest scalar seaborn skit-learn svm xgboost

Last synced: 4 days ago
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In this i tried to design a model that can predict the price of stock using different methods and algorithms.

• Host: GitHub
• URL: https://github.com/ksharma67/ibm-stock-predication-wiith-eda
• Owner: ksharma67
• Created: 2022-10-14T19:35:33.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-10-14T19:39:39.000Z (over 2 years ago)
• Last Synced: 2024-12-25T14:07:06.370Z (about 2 months ago)
• Topics: bullish-signal, death-cross, decision-tree, eda, golden-cross, gradient-boosting, knn, machine-learning-algorithms, matplotlib, numpy, pandas, prediction, python, random-forest, scalar, seaborn, skit-learn, svm, xgboost
• Language: Jupyter Notebook
• Homepage:
• Size: 494 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# IBM-Stock-Predication-wiith-EDA

I tried to design a model that can predict the price of the stock using different methods and algorithms such as Exploratory data analysis (EDA) of Dataset, KNN, Decision Tree, Feature Scaling, Gradient Boosting, SVM, XG Boost, and Random Forest with two different strategies.