More and more industries are undergoing digital transformation and seeing substantial results from the adoption of modern technologies. Agriculture and farming are increasingly relying on automation to make farms and cooperatives more efficient, reduce the amount of manual labor and be able to analyze data to model and forecast future production. The advancements in robotics are applied in harvesting, watering, seeding. There have also been interesting experiments with drones, autonomous tractors, and other farming tools.
In addition to decreasing the number of mundane manual tasks for agriculture workers, innovations such as Machine Learning Automation models or Artificial Intelligence can help businesses deal with their data in an efficient way, minimizing operational costs and improving analytics, streamlining processes, and enabling farm owners and administration to focus on the strategic tasks at hand. …
Our expertise ranges from classificators to anomaly detection to data-based prognostics and our team ranges from 5 to 25 years of experience. Our diversity in experience and services makes us the best to solve our client's problems. We focus on creating disruptive data solutions so you can focus on brighter horizons.
It’s due to our successes that we have been recognized as a 2019 Clutch Leader in the Ukraine developer category!
“As in any consulting business, recommendations and referrals play a very important role for MindCraft. Many of our clients came through recommendations from our other clients. That is why in 2019 we decided to find an independent platform where our clients could leave their honest feedback about working with us, about the things we could improve; a platform where we could showcase our projects and our activities. Clutch seemed to perfectly match our goals.” …
After reading this article you will:
Who will benefit from this knowledge:
We defined a few key directions to explore, which will help you efficiently implement Data Science…
Subject: Special Offers Evaluation for a Retailer in Automotive
Data Science Areas: Machine Learning, Data Processing, Predictive Analytics, Business Intelligence, Business Forecasting, Sales Forecasting
Tools: Python, Pandas, Numpy, Tkinter
Summary: For a dealer in the car parts retail business, a team of machine learning developers at MindCraft created a predictive sales analytics solution. It automatically measures the profitability of buying items from the special offers lists. The solution evaluates the possible sales rates and estimates the discount. It provides invaluable marketing insights and helps to make smart business decisions.
Dealing in the car parts business, our customer receives a lot of special offers. In this industry, there are millions of items and a special offer document can contain tens of thousands of items. …
Subject: Sales Forecasting Using Machine Learning
Data Science Areas: Time Series Analysis, Data Processing, Machine Learning, Supervised Learning, Predictive Analytics, Business Forecasting, Business Intelligence, Demand Planning
Tools: Python, Pandas, Matplotlib, Statsmodels, Sklearn
Summary: The Data Science team at Mindcraft developed a Python-based Machine Learning solution for Sales Forecasting. Developed for a client in the Automotive industry, the product analyzes Sales Time Series data, predicts buying behavior and helps to boost Business Intelligence in Retail.
Our client is a wholesale retail company dealing in car parts. They addressed MindCraft with a request to develop a Machine Learning model that would predict the sales rate of the items in stock. The solution would help optimize their stock, maximizing revenue per each dollar invested in goods. Since there were tens of thousands of items, the sales forecasting could never be done manually. …
Active Learning is a semi-supervised technique that allows labeling less data by selecting the most important samples from the learning process (loss) standpoint It can have a huge impact on the project cost in the case when the amount of data is large and the labeling rate is high. For example, object detection and NLP-NER problems.
The article is based on the following code: Active Learning on MNIST
#load 4000 of MNIST data for train and 400 for testing
(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()
x_full = x_train[:4000] / 255
y_full = y_train[:4000]
x_test = x_test[:400] /255
y_test = y_test[:400]
x_full.shape, y_full.shape, x_test.shape, …
In the second half of September 2018, an international project GGULIVRR@Lodz-2018 (https://ggulivrr.uni.lodz.pl/ ) took place in Łódź, Poland, gathering more than 75 participants from Poland, Belgium, Finland, France, Ireland, Portugal, Slovenia, and Ukraine. During those two weeks, our R&D Director Mykola Kozlenko was taking part in the project as a mentor for one of the international teams.
The project is organized by the Faculty of Physics and Applied Informatics of the University of Łódź. This is a multidisciplinary project that combines scientific work, practical orientation and teamwork of designers, programmers, marketers. …
Partners often reach out to MindCraft with a request to help create a demand for their services. And this task sounds very appealing to us. After conducting a careful research into our clients’ services and the selection of effective solutions we were able to generate an important knowledge pool of means that can be really effective in the achieving of this goal and those that cannot.
With the help of the information obtained and our thorough work, we have developed an engine based on Machine Learning and Computer Vision for one of customers. The potential of the engine is immense since it enables increasing the demand for the client’s business and significantly boosting sales rates right from the first quarter the engine is in use. …
Our thoughts about how to join in Data Science.
If you are a developer in an IT company or if you would like to become a developer in the future, if you study applied math at university, or if you are an expert in statistics, an analyst who likes to work with data, or just a technical person interested in IT trends, then you will definitely find this article interesting and useful.
Today, founders of Mindcraft.ai CEO Andy Bosyi and R&D Director Mykola Kozlenko,will help you to delve into the technical side of this science and tell you what is hidden behind Data Science, what you need to know and learn from the data scientist, which technologies are now leading Data Science…
Subject: Automated Document Classification, Document Capturing, Data Extraction
Business Areas: Banking, FinTech, Retail
Data Science Areas: Computer Vision, Machine Learning
Tools: Python, Tensorflow, Sklearn, Tesseract
Summary: The Machine Learning team at MindCraft helped to automate the document capture and recognition for a client in the Banking industry. The system can process documents for any domain and containing any kind of content, from handwritten text to fields and tables.
Our client has been in the market of banking and finance services for over 10 years. They asked our team of data scientists to come up with a machine learning solution to simplify their document recognition and classification procedure. Every day the company had to process a few thousands of units of business data. A substantial team of people performed this manually, which was both time-consuming and costly. …