Stock Price Prediction Using Python & Machine Learning (LSTM).
In this video you will learn how to create an artificial neural network called Long Short Term Memory to predict the future price of stock.
NOTE: In the video to calculate the RMSE I put the following statement:
When in fact I meant to put :
You can use the following statements to calculate RMSE:
1. rmse =np.sqrt(np.mean(((predictions- y_test)**2)))
2. rmse = np.sqrt(np.mean(np.power((np.array(y_test)-np.array(predictions)),2)))
3. rmse = np.sqrt(((predictions – y_test) ** 2).mean())
In this tutorial, we implement Recurrent Neural Networks with LSTM as example with keras and Tensorflow backend. The same procedure can be followed for a Simple RNN.
We implement Multi layer RNN, visualize the convergence and results. We then implement for variable sized inputs.
Recurrent Neural Networks RNN / LSTM / GRU are a very popular type of Neural Networks which captures features from time series or sequential data. It has amazing results with text and even Image Captioning.
In this example we try to predict the next digit given a sequence of digits. Same concept can be extended to text images and even music.
Find the codes here
GitHub : https://github.com/shreyans29/thesemicolon
Good Reads : http://karpathy.github.io/
Check out the machine learning, deep learning and developer products
Data Science book Recommendations :
Python Reinforcement Learning : https://amzn.to/30MSlIU
Machine Learning : https://amzn.to/30OuRmw
Deep Learning Essentials : https://amzn.to/336opJ9
Deep Learning : https://amzn.to/2OoSY8J
Pattern Recognition : https://amzn.to/2MgUveD
Pattern Recognition : https://amzn.to/2ViNWfJ
Deep Learning : https://amzn.to/2Vp3UVC
Reinforcement Learning : https://amzn.to/2LQz0SY
Python Deep Learning : https://amzn.to/2LQvXKj
Machine Learning : https://amzn.to/2Ml6NSX
Laptop Recommendations for Data Science :
Asus : https://amzn.to/338roku
MSI : https://amzn.to/2OvdDIB
Lenovo : https://amzn.to/2OmpzMr
Dell : https://amzn.to/2OnFeet
Asus : https://amzn.to/2LPQqyZ
Lenovo : https://amzn.to/2AS7XQx
Computer Science book Recommendations :
Algorithms and Datastructures : https://amzn.to/3555P69
C programming : https://amzn.to/2nnuYrJ
Networking : https://amzn.to/2ItnOcN
Operating Systems : https://amzn.to/2LOjXsI
Database Systems : https://amzn.to/32ZqczM
Computer Systems Architecture : https://amzn.to/336IxuM
Database Systems : https://amzn.to/2nntKN9
Operating Systems : https://amzn.to/2Vj1tUr
Networking : https://amzn.to/2IrnpHL
Algorithms and Datastructures : https://amzn.to/358jA3S
C programming : https://amzn.to/2oXKXNm
Head First Java – https://www.amazon.com/gp/product/0596009208/ref=as_li_tl?ie=UTF8&tag=everythingc06-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=0596009208&linkId=58082f233879197beb1aeb73b03c1ed8
Practice Problems in Discrete Mathematics -https://www.amazon.com/gp/product/0130458031/ref=as_li_tl?ie=UTF8&tag=everythingc06-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=0130458031&linkId=e6c98555ea0342d902afda0221a1a8fb
In this tutorial, we’ll see an example of deep reinforcement learning for algorithmic trading using BTGym (OpenAI Gym environment API for backtrader backtesting library) and a DQN algorithm from a medium post (link below) to interact with the environment and does the trading.
Access to the code: https://gist.github.com/arsalanaf/d10e0c9e2422dba94c91e478831acb12
Learn how to select correlated pairs to build a long-short hedged pairs trading position with Python in QuantConnect.
Sponsored by QuantConnect
In this video I describe the results of a 14 hour trade bot on binance trading the coin pair ZEN-BNB. We see a profit of 4.4% over 14 hours, beating the ‚market‘ of .7%. Also discussed is the threshold settings for Neural Network strategy on Gekko.
Join Crypto Trading Bot discussion:
Twitter: http://www.twitter.com/BlockchainEng Video Rating: / 5
** Neural Networks for Trading: https://quantra.quantinsti.com/course/neural-networks-deep-learning-trading-ernest-chan ** START FOR FREE!
This Quantra video on Deep Learning in Python will give you an overview of a course for quants and traders to implement neural network and deep learning in financial markets. Offered by Dr. Ernest Chan, learn to use advanced techniques such as LSTM, RNN in live trading. Below are the topics covered in this course:
1. Neural Networks Trading Strategy
2. Adding deep learning layers
3. Recurrent Neural Networks
4. Long Short Term Memory units
5. Cross Validation in Keras
6. Live Trading models
Subscribe to our channel to get video updates. Hit the subscribe button above.
Quantra is an online education portal that specializes in Algorithmic and Quantitative trading. Quantra offers various bite-sized, self-paced and interactive courses that are perfect for busy professionals, seeking implementable knowledge in this domain.
Find more info on – https://quantra.quantinsti.com/
Like us on Facebook: https://www.facebook.com/goquantra/
Follow us on Twitter: https://twitter.com/GoQuantra Video Rating: / 5