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Does anyone know of any courses etc for teaching people how to learn how to apply technical analysis and trading mechanics to the development of an automated trading algorithm?
I'm a regular at Quantopian, and attended the most recent Quantcon. They had some seminars, but largely it's a huge topic (like learning "surgery") because of the multiple disciplines involved.
Different languages, different levels of profeciency with those languages, different time frames, different securities, and a general air of secrecy where no one wants to share strategies.
For a programmer, I'd focus on API integrations (if you need that, some strategies run once a month then you punch in your trades manually). For a noob-programmer, I'd focus on programming skills in C#.
Sorry for being so broad, but like I said it's a huge topic. There's miles between a long gamma hedge fund doing managed futures and an HFT with custom hardware chips.
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I have some job experience in machine learning, specifically in the branch of computer vision. However, when I develop at work I use tools that abstract away the compute and storage via some cloud API.
Now, I want to develop a deep NN in my spare time and on my PC - I cannot use the work's resources and code.
What is the best setup, from your experience, for compute and storage I can get on a budget? To be specific, I am aiming to:
have ~1M samples of data - images of decent size, let's say 500X500.
try a variety of models, CNN and transformer architectures included.
Of course, I want training to be done in reasonable time (up to a day).
I can save checkpoints and resume if that helps with budget but preferably I will want to train one time each model.
I know some people use Google Colab which offers GPU access. What are the pros and cons and what alternatives are out there?
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I am looking for beginner Machine Learning Linear Regression problems. I searched in Kaggle, but couldn't find a proper one. Can you please suggest me a beginner problem from Kaggle, or from any other platform?
Thanks in advance.
Kaggle has tons of linear regression notebooks and datasets to learn from, most popular ones are probably about house pricing (given certain house features predict it's price).
Here's a new one I'm looking forward to solve:
Ben & Jerry's flavours and ratings ---> products.csv
The main goal would be predict wich ice cream flavours are better accepted based on it's ingredients.
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I am trying to do a paper about the Machine learning been applied in NLP. Can you guys please suggest me applications that have already used the Machine learning with the NLP?
The list is broad since machine learning is becoming more and more mainstream.
Regarding text, images and video, a good list of APIs would be:
AT&T Speech, IBM Watson, Google Prediction, Wit.ai, AlchemyAPI, Diffbot and I guess Project Oxford as well.
Hope it helps.
If you want something generic you can use this tutorial: http://www.cs.columbia.edu/~mcollins/papers/tutorial_colt.pdf
It is probably not the more recent information but you could find it useful if you start to learn ML methods for NLP.
As it is mentionned in this tutorial, ML methods are generally linked to the NLP task (Information Extraction, Machine Translation, etc.).
IBM Watson project is an example of platform that uses NLP and ML.
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I'm a recent grad with a CSS degree and I never had a chance to take a course on distributed systems, but have progressively become interested in the topic. I would love to dive into the subject head-first in hopes of beginning my career as a software developer in that field. I've taken an Operating Systems course and have knowledge of multithreaded programming, along with elementary knowledge of distributed systems concepts, but that's about as close as I got to the subject, which isn't close at all.
Does anyone know a good place to start learning about the subject for someone with a CSS degree?
Do I really need a strong background in distributed systems specifically to get an entry-level job or do you think there are companies willing to hire people with strong programming skills but not necessarily strong knowledge of distributed systems?
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I would like to know any prices you have heard of for one-to-one conversion projects from Cobol code to a modern language. We are talking about programs with several hundred thousand lines of code.
I imagine it would be very difficult to accurately cost a conversion of this nature. Apart from the code, and understanding the business processes, you would also have to factor in changes for the new environment, running batch programs, print spooling, etc.
Instead of converting, have you checked out the possibility of changing the COBOL environment, i.e. running under .NET or JVM.
And COBOL is a modern language :-)