GitHub - jainsee24/Stock-Price-Prediction-Machine-Learning: This is 6th and last capstone project in the arrangement of the undertakings recorded in Udacity-Machine Learning Nano Degree Program. Venture firms, mutual funds and even people have been utilizing monetary models to more readily comprehend market conduct and make beneficial speculations and exchanges. An abundance of data is accessible as chronicled stock costs and friends execution information, reasonable for AI calculations to measure. Could we really foresee stock costs with AI? Financial backers make instructed surmises by dissecting information. They'll peruse the news, study the organization history, industry patterns and different bunches of information focuses that go into making a forecast. The common speculations is that stock costs are absolutely arbitrary and unusual yet that brings up the issue why top firms like Morgan Stanley and Citigroup enlist quantitative examiners to fabricate prescient models. We have this thought of an exchanging floor being loaded up with adrenaline implant men with free ties going around hollering something into a telephone however nowadays they're bound to see columns of AI specialists unobtrusively sitting before PC screens. Truth be told about 70% of all orders on Wall Street are currently positioned by programming, we're presently living in the age of the calculation. This venture uses Deep Learning models, Long-Short Term Memory (LSTM) Neural Network calculation, to anticipate stock costs. For information with time periods intermittent neural organizations (RNNs) prove to be useful however late explores have shown that LSTM, networks are the most famous and valuable variations of RNNs. I have utilized Keras to assemble a LSTM to foresee stock costs utilizing chronicled shutting cost and exchanging volume and envision both the anticipated value esteems after some time and the ideal boundaries for the model.

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This is 6th and last capstone project in the arrangement of the undertakings recorded in Udacity-Machine Learning Nano Degree Program. Venture firms, mutual funds and even people have been utilizing monetary models to more readily comprehend market conduct and make beneficial speculations and exchanges. An abundance of data is accessible as chro…

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Name		Name	Last commit message	Last commit date
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LinearRegressionModel.py		LinearRegressionModel.py
Project proposal.pdf		Project proposal.pdf
Project_Report.pdf		Project_Report.pdf
Stock_Price_Predictor.ipynb		Stock_Price_Predictor.ipynb
data_visualization.png		data_visualization.png
data_visualization_benchmark.png		data_visualization_benchmark.png
data_visualization_lstm_basic.png		data_visualization_lstm_basic.png
data_visualization_lstm_improved.png		data_visualization_lstm_improved.png
googl.csv		googl.csv
google.csv		google.csv
google_preprocessed.csv		google_preprocessed.csv
lstm.py		lstm.py
preprocess_data.py		preprocess_data.py
results.html		results.html
stock_data.py		stock_data.py
visualize.py		visualize.py

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LinearRegressionModel.py

LinearRegressionModel.py

Project proposal.pdf

Project proposal.pdf

Project_Report.pdf

Project_Report.pdf

Stock_Price_Predictor.ipynb

Stock_Price_Predictor.ipynb

data_visualization.png

data_visualization.png

data_visualization_benchmark.png

data_visualization_benchmark.png

data_visualization_lstm_basic.png

data_visualization_lstm_basic.png

data_visualization_lstm_improved.png

data_visualization_lstm_improved.png

googl.csv

googl.csv

google.csv

google.csv

google_preprocessed.csv

google_preprocessed.csv

lstm.py

lstm.py

preprocess_data.py

preprocess_data.py

results.html

results.html

stock_data.py

stock_data.py

visualize.py

visualize.py

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