Reduce loss, incress accuracy in sequence! [Machine learning: Deep Learning: Keras: LSTM]
$30-250 USD
Pagado a la entrega
This is a very simple problem, I'm looking for someone with experience with LSTM or any other algorithm (like it could be XGB / Random Forest) in order to improve the performance of a deep learning network.
Dataset: 520,000 records.
Attached to this project, you'll find the sample & training data + the script which is already created.
The main goal, is to know if the value will to know if the next value will be bigger than 20, or lower. Even the chances are good.
(1) You'll need to modify it to read from CSV instead, replacing "read_sql_query" for "read_csv"
(2) I've been trying only with one column, which is "value", and that's (included "[login to view URL]")
(3) I've also included a 2ND CSV file including "id" + "value" + "creacion" (included in "[login to view URL]")
Feel free to ask for any questions! Anyone who can increase the rate, specially, predict when the value will be lower than 20 is already good enough!
Nº del proyecto: #17161598
Sobre el proyecto
14 freelancers están ofertando un promedio de $204 por este trabajo
Experienced data scientist who has extensively used LSTM, CNN and other linear, decision tree based algorithms for a variety of projects. Going through the provided information I think that the stated goal can be accom Más
Hi I am a very experienced statistician and academic writer. I have completed several PhD level thesis projects involving advanced statistical analysis of data. I have worked with data from several companies and have d Más
Since you have invited me to bid yourself, i guess we can discuss the details of the project on chat if you would like to.
I am an expert in Data science, I've done a lot of projects in Machine learning involving data preparation, data visualization, building classifiers and regression model using Python, R and Matlab contact me for furt Más
hey, I hope you are having a base script for the same. kindly share the same so that I can actually work on what has to be changed to increase the accuracy of your prediction in lstm.