Machine learning and neural networks

We help companies to solve complex business tasks and optimize workflow using machine learning technologies.

What a neural network consists of

The foundation of each neural network is built upon the following three pillars:

  • data;
  • attributes;
  • algorithm.

Data

It is the most important part because this is the foundation upon which the neural network is built. Those can be letters from the mail that have to be filtered or equipment sensors readings by which its behavior at the following moment can be forecasted. Those can be data of any type.

Attributes

By its nature, those are the characteristics that have been selected from the data. For example, the price of shares, car mileage, or the number of transactions in the system.

Algorithm

The algorithm is an important component of this task. The precision and speed of learning depend thereon. However, it should be understood that if the data are not properly prepared, no algorithm will help!

Why your business needs a neural network

The scope of application of machine learning has long gone beyond the IT area. Nowadays, machine learning and neural networks are in use in almost all business areas. The list of tasks performed by the neural networks is extremely broad: from the improvement of the video quality to the predictive analytics.

Estimation of the employees/strategy/sales efficiency

Estimation of efficiency helps to understand how well your enterprise operates and also helps to adjust the strategy or the processes to increase the profits.

Customers clustering

Knowing your customer profile, the company can develop marketing programs much more effectively and change the product to meet the customer’s needs.

Content customization

The customized content provision helps to retain customers better, making a loyal customer out of a plain customer. Furthermore, the level of involvement grows, which increases the average purchase amount.

Urban environment optimization

Helps to optimize the public urban transport routes. Carry out the passenger flow analysis. Increase the roads and interchanges safety.

Process flow optimization

The complex methods allow understanding of how effective the production is. And also to create the forecast models for the optimal control of the process flows.

Prediction of the delivery time/order manufacturing

Analysis of the accumulated big data on the filling of orders allows planning the logistics more precisely, which ultimately has a favorable effect on the general economic performance.

And hundreds of various variants of use of the machine learning and neural networks...

Stages of a neural network building

We can perform any separate stage or build a full-cycle neural network model.

Stage 1

Data collection

The more data you have, the more precise the result of the work of the neural network will be.

Stage 2

Data analysis and origination

We analyze and structure the data to compose the correct model.

Stage 3

Neural network training

We develop algorithms and provide neural network learning in accordance with the data prepared.

Stage 4

Introduction of the neural network

We introduce the neural network into the customer’s business processes.

Our tools

We have a practical knowledge of all the most popular libraries for machine learning.

TensorFlow

Keras

scikit-learn

https://scikit-learn.org/stable/

OpenCV

pandas

NumPy

SciPy

Matplotlib

Order the development of a neural network

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