Need Python Machine Learning Expert to learns the data distribution during normal every-day execution and signals when that output is anomalous with respect to the past.
Most importantly can great good GUI and amazing graphs
This is my proposal
Milestone 1. Create python program to collect the data from snort and other analyzers and then merge all the datas to a jason format. (API Endpoints)
Milestone 2. Add a feature in the program that read a jason file, get and show the unlabelled data, then a user can label the data manually.
Milestone 3. Train and test the data using ML. Get the best classifier and hyperparameters according to the testing accuracy.
Milestone 4. From the best classifier model obtained above, modify the python program by embedding the prediction after a new data coming.
Milestone 5. Create separated program that will update the classifier model after N new datas are labelled or every certain period e.g. re-train should be done twice a day or maybe once an hour. According to the rate of incoming data and the speed of training.
30 фрилансеров(-а) готовы выполнить эту работу в среднем за $343
Hi! I am deep learning developer. I can use any python deep learning language such as tensorflow, torch, caffee, keras, paddle and so on. I also have deep knowledge in machine learning. You can test me. Thank you.
Hi there, I am a talented python dev, and I think I can handle this task perfectly. Please give me your chance, I look forward to hearing from you. Regards!
Hello. I am a deep learning expert. I can do this project wonderfully. I will suggest how to implement this project using deep learning via chat. Feel free ping me. Thank you.
Hi, I have +5 years of experience dealing with machine learning algorithms and worked on multiple projects in this field, Please contact me to discuss more. Have a nice day