Software development and data science team for you
Quant Coding is a software development and data science team that can develop web, desktop, and mobile applications for your business. We are also very experienced in data science, machine learning, and artificial intelligence and provide expert services in this area. Pick Quant Coding as your software and data science development company and you will not be disappointed. We deliver premium service at good value rates.
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Scraping scripts with Scrappy
For a young startup from the USA, we have completed a fairly challenging and massive scrape of online data. We have collected over 60 million data records from an online source and written this to the client database. For the project, we have used the robust Python scraping framework Scrapy utilizing a lot of the extensions available and building our custom extensions as needed. This involved making complex requests while maintaining some sort of “state” with the server through cookies and other items all that on separate proxies or “sessions” to allow timely completion of the job. We have used SQLALchemy, Pandas, and other helper libraries in Python to complete this job. In the end, the client was very happy with the results and the overall work on the project.
Genetic algorithm trading simulations
For one of our existing clients, we have completed a Genetic Algorithm script that would test different variations of a trading simulation. The algorithm was trying to optimize and narrow down the set of inputs that would produce maximum desirability (fitness) results of the simulations. The algorithm was deployed to run on AWS EC2 and utilize as many instances as are needed to complete the simulations in a timely manner. Connections with manager nodes were established using Web Sockets. Some of the fitness calculations were vectorized to save on computation costs for the client.
Machine learning classifier for delayed flights
Stock market strategy backtesting application
We have built a stock market back-testing web application that runs on scalable AWS infrastructure. The core back-testing engine of the application is running on Quantstrat in R and allows ample possibles to our client to extend the back-testing platform with additional options for the users. Users are able to select a stock, define their initial equity, select technical indicators to use, and define parameters for those technical indicators. Then the user can define their entry and exit signals based on the technical indicators or take profit, stop-loss, and trailing-stop-loss % thresholds from the price. The application as we have built it works with over 53 indicators and provides extensive results to the users including full order books, transactions, trades as well as meaningful charts and summary results. The application also included a professionally designed front-end and a back-end to service the user requests. The back-end services users requests using the scale-able EC2 AWS infrastructure. This allows our client to grow and scale his business unlimited by cloud computing resources while at the same time providing significant cost savings by utilizing cloud computing servers only when needed and as-needed. We have used diverse technologies on this project: from AWS, Python with Flask, R with Quantstart as well as JavaScript VueJS for the front end. In addition, it involved integrating with Elementor Widgets in WordPress.
Reviews
the project
Data Collection & Analysis for Vacation Rental Developer
"Their knowledge about the technology and their communication skills were impressive."
the reviewer
the review
The client submitted this review online.
Please describe your company and your position there.
CEO @ Ghosal Real Estate Holdings LLC. We develop high end vacation rentals and use technology to give us an edge!
For what projects/services did your company hire Quant Coding, and what were your goals?
We were looking to get competitive market information about overnight rental rates and occupancy. Once this information was collected from the internet, we would analyze this data to provide us with optimal rental rates for specific days of the year.
How did you select Quant Coding and what were the deciding factors?
They seemed to be aggressive in the bidding process and seemed to know exactly what they were doing. Communication was also easy since they speak english fluently.
Describe the scope of work in detail, including the project steps, key deliverables, and technologies used.
We had multiple rental companies to be scraped. This was done in three phases. We provided them the exact format in which the information had to be collected. Once this was done, they developed a script that would run every night and deliver the results to our mailbox.
How many people from the vendor's team worked with you, and what were their positions?
One
Can you share any measurable outcomes of the project or general feedback about the deliverables?
Project was delivered on time and within budget
Describe their project management style, including communication tools and timelines.
Mainly communication via messaging on Upwork.
What did you find most impressive or unique about this company?
Their knowledge about the technology and their communication skills were impressive.
Are there any areas for improvement or something they could have done differently?
I have not tested them in wider area of technology. So it is hard for me to say how they will do in other areas. But they did well in the specific areas that I used them for.
the project
Predictive Data & Analytics for IT Business Service Provider
"They use a creative method to sort out data framework and modeling."
the reviewer
the review
The client submitted this review online.
Please describe your company and your position there.
CEO and co-founder
For what projects/services did your company hire Quant Coding?
Data engineering and Machine Learning algorighthms.
What were your goals for this project?
Collect data, reformat, structure data, build models, train, test and productionize.
How did you select Quant Coding?
Upwork
Describe the project in detail.
Collect data, reformat, structure data, build models, train, test and productionize.
What was the team composition?
1-2 data engineers and 1 data scientist.
Can you share any outcomes from the project that demonstrate progress or success?
Very competent, very responsive, independent, knowledgeable, creative and professional.
How effective was the workflow between your team and theirs?
Good to very good.
What did you find most impressive about this company?
They use a creative method to sort out data framework and modeling.
Are there any areas for improvement?
I wish they provided a more sustained communication thread with my team.
Quant Coding did a spectacular job. The project was a success and they were able to deliver the tasks on time. The team was knowledgeable and communicative.