Build A Stock Prediction Program

Write a Stock Prediction Program In Python Using Machine Learning Algorithms

Disclaimer: The material in this video is purely for educational purposes and should not be taken as professional investment advice. Invest at your own discretion.

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►Machine Learning Articles:
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(2)Decision Tree Classifier:

(3) Doing Machine Learning Without Code:

(4) A Simple Machine Learning Program:

(5) Machine Learning Simplified:

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►Helpful Resources:

[thenightmareomg]

Dude, you rock! That was an awesome demo of how to build a basic ML program! I've been learning ML for a few weeks now using Python etc and of all the demos and explanations I've seen, yours is totally standout. You speeded up a little about halfway through and I kinda got lost a little but after re-watching a couple of times, I've got it!

[philmarlin]

Instructions not clear. Lost all of my money to a pyramid scheme

[crypticnomad]

to remove the NaN elements you can simply do: df = df.dropna(). To get a np array from each column you can simply do df['column'].values. So you could have done:
df = df.dropna()
X = df['Adj. Close'].values
y = df['Prediction'].values

[djx]

Can someone help me clarify:

I think something is incorrect with the model prediction. I just followed this tutorial, but the model's prediction for the next X days mirrors the actual past X days of the stock price. You can notice the same in the video at 33:25 and 34:25. When he prints the x_forecast and lr_prediction, the values match. But this is incorrect if we are attempting to forecast the next X days. The first value of lr_prediction should start closer to the final value of x_forecast. My model that I have built using this tutorial does the same, so I think something is definitely incorrect here.

Thanks for any help/clarification.

[jonahkollenberg]

This is great, thanks! Instructions are so good I even convinced some guy to invest all his money in my pyramid scheme

[kevintanyj]

Might be a little late to this discussion, but if anyone wants to import the data for majority of the stocks, look no further than yfinance, which is short for yahoo finance. You can install this package and load any stock data with a simple query

[goldy]

How could you split the data randomly it's a trend there should be splitting the first 80 and 20 to prevent data shuffling

[Ficsher]

Quandl has stopped supporting WIKI since Apr 2018. Prices are not updated since then.

[William_sJazzLoft]

A radial basis function is a real-valued function whose value depends only on the distance between the input and some fixed point.

[josevalencia]

This was very interesting! Useful YTube Reading at 2 a.m.

[chandlerlabs]

Great job, thank you;-) I have not "wrote code" in over 20 years, by choice, but your instruction methods are excellent! From knowing "zero" about Python, to getting "up and running", I sure can contribute to your video series! Thank you for the knowledge transfer and keep up the good work.

[davidmathew]

Why is your GitHub not in the description like you said?

[hsuani]

saw that you have gone through the tutorial well.i am happy for you. i have one question at 6:34.i have same code as its.but collab return LimitExceededError to me.why? and how can i fix it.i will be grateful if anyone can answer me

[gamble]

Why is the date 2018-03-21? How do we adjust the date further out to today?

[MichielDeSnuyter]

Python thought it would be a good idea to invest my pension in Prince Habib Habibi IV of Nigeria.

[William_sJazzLoft]

The quandl api apparently does not track stocks that are small-cap, micro-cap, or nano-cap. Basically, anything that might be considered a 'penny stock' is not tracked. Whatever is plugged in has to be $ 3 billion in market cap or greater.

[Mrabhijeetjain]

What is the p-value of your prediction/model ?

[traderdescomplicado]

Great Video! I try the model with my data and I got the worse result for the test (SVM -0.0072) and (LR 0.358), any ideas why it happened?

[milikest]

Great way to loose money. In the model if you don't use Elliot Wave count, fib levels, correction methods, rsi, macd, ema-sma and resistent and support lines then most likely you will lose money. Accuracy can be high in this time, but it is not important. Take a look of BTC/USD chart. Use the 01 April - 17 December 2017 as your train data. Will your model predict the collapse after december 17?

[charlesbacon]

Wow - what a cool tutorial, amazingly well presented. And you take the time to comment the code which i really [REALLY] appreciate. :)
I was able to follow in colab. For some reason, my AAPL prices were in the range of 60-70 unlike yours in the 200s - so i'm confused about the data source it uses - actual prices are nearer $100... probably finger trouble on my side.! Never mind - i will sort - it worked a treat - and great into to Colab.
Also, I didn't need to reshape X_test - it was already at (1, 60, 1), and in fact - reshaping throw an exception.
I look forward to extending this... I'll be checking out your other videos :)