Providing machine learning consulting & artificial intelligence services, we start with goal setting and analysis of business processes to help companies see machine learning capabilities matching their business goals.
By leveraging strong machine learning expertise, we handle all data-related processes, including data collection and preprocessing, to prepare datasets for effective modeling. We choose/create an optimal ML model, evaluating its accuracy to deliver a production-ready solution tailored to specific business needs.

Our experts develop machine-supervised, unsupervised, and reinforcement learning solutions to deliver guaranteed value to clients.

MACHINE LEARNING COMPETENCIES

Time Series Forecasting

With machine learning models trained on historical data, the tasks that demand forecasting, price predictions, seasonal fluctuations, and trends are solved much easier. Time series forecasting should become an integral part of the workflow for companies operating on markets with high volatility.

  • Time series classification
  • Confidence interval estimation
  • Stock market prediction
  • Time series clustering
NLP (Natural language processing)

CodeIT Machine Learning specialists create applications to recognize, process, and interpret unstructured written and oral natural language to extract meaningful information and value. We help companies from various industries improve their daily workflows using NLP outcomes.

  • Machine translation
  • Question answering
  • Sentiment analysis
  • Speech recognition
  • Semantic analysis
Computer vision

Based on machine learning algorithms, image analysis solutions can understand visual content and extract relevant information pertaining to object identification, recognition, and evaluation.

  • Face recognition and modeling
  • Biometric verification
  • Image reconstruction
  • Video analysis
  • Activity recognition
  • Gesture and emotion recognition
Recommender Systems

Leveraging machine learning capabilities, our data science team implements recommender systems critical in delivering personalized customer experience. Recommender systems are indispensable for e-commerce sites due to their ability of offering relevant suggestions to users.
Thus, we help companies win their customers’ loyalty, significantly increase conversions and boost revenue.

  • Collaborative filtering
  • Content-based filtering
  • Hybrid recommender systems
Predictive Analytics

Predict market trends, behavior patterns, product sales, and more by extracting and analyzing past and present data. Predictive analytics will help predict and prevent potential issues, assess risks by ensuring better decision making.

  • Predictive models
  • Descriptive models
  • Decision models
Anomaly Detection

The goal of anomaly detection is to identify unusual objects, events, or behavior in datasets that differ from the majority of data. The application of anomaly detection techniques is of great value in detecting intrusions, fraud, security issues, text data anomalies, health problems.

  • Unsupervised anomaly detection
  • Supervised anomaly detection
  • Semi-supervised anomaly detection

Get your custom machine learning solutions

Technology stack

tensor flow Tensor flow
scikit learn Scikit Learn
keras keras
python python
matplotlib Matplotlib
Jupyter Notebook Jupyter Notebook
Pandas Pandas
Numpy Numpy

Machine Learning Workflow

We can work at some stages in parallel
1

1. Business task understanding

  • Define project requirements
  • Define task objective
2

2. Data Exploration

  • Discover data insights
  • Plot graphs, visualization
  • Domain knowledge reception
3

3. Data Preparation

  • Data cleaning
  • Feature extraction
  • Feature selection
  • Build pre-processing pipeline
4

4. Modeling

  • Choose model
  • Define loss function and metrics
  • Parameter tuning
Being an iterative process, ML model development implies taking a step back to model accuracy or changes in the solution approach when getting results/performance scores.
5

5. Evaluation / Validation

  • Performance scores estimation
  • Validation and test datasets evaluating
  • Cross-validation
We can work at some stages in parallel.
6

6. Deployment

  • Continuous model delivery
  • Prepare production-ready solution
  • Metrics logging
  • Performance monitoring
Being an iterative process, ML model development implies taking a step back to model accuracy or changes in the solution approach when getting results/performance scores

MACHINE LEARNING PLATFORMS WE USE

Google ML

Google ML

As machine learning service providers, we've been following the development of ML solutions from Google and their cooperation with companies such as DeepMind for a long time. Our experts use TensorFlow not only to do scientific research but to develop machine learning solutions for your business.

Azure ML

Azure ML Studio

Another great platform, this time from Microsoft. One of the favorite cloud platforms of our specialists, which they use to quickly build machine learning products and grant ML as a service culture within our company.

AWS Machine Learning

AWS Machine Learning

Our experts prefer the Amazon platform due to the fact that they provide the largest number of machine learning functionality. In addition, the cloud-based nature of the platform allowing rapid install and setup. We use SageMaker service to create ML models that meet your business logic and bring you useful deep learning data.

faq

What problems can machine learning solve?
Machine Learning is solving a huge number of problems right now. The range of this technology application is truly immense: from spam identification and customer segmentation to predicting behavioral patterns\trends prediction and video materials recognition.
Is machine learning still in demand?
Of course, and it will be in demand for a long time in the future. However, one should not forget about such a phenomenon as hype, but nevertheless, it is safe to say that at the moment the labor market of Machine Learning specialists is up-and-coming.
What programming language is used for machine learning?
The most popular languages among machine learning specialists are Python, C/C ++, R, and Java.

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It's time to apply machine learning intelligence to your products.