In this video I'll focus on Technical Analysis of the stock market! This is a multipart tutorial series that will show you how to use Python to analyze and search for chart patterns that you can use to make stock market predictions.

I gave you a taste of the potential a while back when I recommended a stock that then went up 300% in 5 days.

I will be using Python and Multiple Data Science libraries in this tutorial to perform Technical Analysis. We will be covering the following :

️ Downloading Realtime Data
️ Candlestick Charts
️ Simple Moving Averages
️ Exponential Moving Averages
️ Making Beautiful Charts
️ Death Crosses
️ Golden Crosses
️ Cufflinks Quant Module
️ Numerous Data Science Libraries
️ So much more

Files Are Here : https://github.com/derekbanas/Python4Finance
[ Look for the File : Technical Analysis.ipynb ]

LIVESTREAMS : https://www.twitch.tv/derekbanas
DISCORD : https://discord.gg/2dkDmpVvgD ( Contact Me Anytime )

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I LIVESTREAM CODE HERE : https://www.twitch.tv/derekbanas
MY DISCORD : https://discord.gg/VckHCAvA ( Contact Me Anytime )

THIS IS NOT INVESTMENT ADVICE
I'm not implying that investing this way will guarantee anything. All investing is risky and you should always take advice from someone who can assess your specific situation. THIS IS FOR EDUCATIONAL PURPOSES ONLY!

MORE DATA SCIENCE VIDEOS

Install for Windows : https://youtu.be/a7Ylbn1ikF0
Install for MacOS : https://youtu.be/2JeoNlCcLOM
Numpy / Pandas / Plotly in 1 Video : https://youtu.be/LOQHYn7BLAg

NumPy in One Video : https://youtu.be/8Y0qQEh7dJg
Pandas in One Video : https://youtu.be/PcvsOaixUh8
Matplotlib in One Video : https://youtu.be/wB9C0Mz9gSo
Seaborn in One Video : https://youtu.be/6GUZXDef2U0
Plotly in One Video : https://youtu.be/GGL6U0k8WYA
Time Series Analysis : https://youtu.be/PpnoNZYce_c
Probability in One Video : https://youtu.be/sEte4hXEgJ8
Statistics in One Video : https://youtu.be/tcusIOfI_GM
Algebra : https://youtu.be/B_WCI_A944E
Linear Algebra : https://youtu.be/6GnzRGJsI3Q

#TechnicalAnalysis #DataScience #Python

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