Machine and Deep Learning Services

When ML-based solutions implemented effectively, Machine Learning allows businesses to unlock optimal capabilities to their realistic problems resolution which leads to tangible business value.

We help organizations to create highly customized solutions based on supervised, semi-supervised and unsupervised learning techniques, improving average accuracy of a ML-models and (or) integrate it to client platforms and systems.

Technologies we use

Machine Learning algorithms

• Supervised learning
• Semi-supervised Learning
• Unsupervised learning
• Reinforcement learning

Neural networks

• Convolutional neural networks
• Recurrent neural networks (LSTM, GRU, etc.)
• Modular neural network
• Radial basis function network
• Generative adversarial networks (GANs)
• Deep Q-Network (DQN)
• Feedforward Neural Network
• Autoencoders (VAE,DAE, SAE, etc.)
• Kohonen Self Organizing Neural Network

Statistics methods

• ARMA
• ARIMA
• Bayesian inference
• Descriptive statistics

Machine Learning libraries & frameworks

• SpaCy
• Keras
• Theano
• Gensim
• Torch
• Caffe
• Apache Spark MLlib
• TensorFlow
• OpenCV
• Scikit Learn

Our ML-solutions Delivery Approach

1 Business Analysis

1. Identifying business problem and expected value
2. Conduct exploratory data analysis
3. Prioritize modeling criteria
4. ML-solution implementation strategy preparation
5. Evaluate risks and success criteria

2 Data Preprocessing

1. Explore, clean, split, and shape the existing data for training enhancing its quality
2. Produce clean and well-curated data which leads to more practical and accurate model outcomes
3. Find and eliminate any data leakage

3 ML-model Building

1. Repeat the process of training the models and evaluating their efficiency until the required accuracy is achieved
2. Tune model hyperparameters for improved performance
3. Adapt the models to new data and discover new patterns
4. Deploy ML models to necessary environment

4 Business intelligence

1. Fully-validated model that you can use to create your software product, complete with AI-features
2. Delivering ML output in an expected format and relevant documentation artifacts
3. Visualize data outputs of model execution to generate actionable business insights and create interactive reports

5 Support and maintenance of ML-models

1. Adopting the models based on changes that are introduced by humans and which could impact the model
2. Relearning the models on a new (not outdated) data

Machine Learning Use Cases We Cover


Computer Vision

Face recognition, detection and modelling
Emotion analysis
Video analytics
Image processing (classification, generation)
Optical character recognition
Damage assessment
Computer-aided diagnosis
Object counting, grading and sorting
Object detection & localization
3D reconstruction


Computer Vision

Face recognition, detection and modelling
Emotion analysis
Video analytics
Image processing (classification, generation)
Optical character recognition
Damage assessment
Computer-aided diagnosis
Object counting, grading and sorting
Object detection & localization
3D reconstruction


Natural language processing

Semantic search
Information extraction
Sentiment analysis
Speech to text conversion and back
Spam filtering
Machine Translation
Question Answering
Text Classification
Chatbots and Dialogue
Emotion Recognition


Natural language processing

Semantic search
Information extraction
Sentiment analysis
Speech to text conversion and back
Spam filtering
Machine Translation
Question Answering
Text Classification
Chatbots and Dialogue
Emotion Recognition


Speech Analysis

3D Face Animation
Speech Recognition
Anomaly Detection
Emotion Recognition
Speech Synthesis
Speaker Recognition and identification
Keyword Spotting
Speech Separation
Spoken Language Understanding
Speech Synthesis


Speech Analysis

3D Face Animation
Speech Recognition
Anomaly Detection
Emotion Recognition
Speech Synthesis
Speaker Recognition and identification
Keyword Spotting
Speech Separation
Spoken Language Understanding
Speech Synthesis


Medical Diagnosis

Medical Image Segmentation
Electrocardiography (ECG) Analysis
Medical Diagnosis
Disease Prediction
X-Ray
Sleep Quality
Cancer Detection
Medical Image Registration
Medical Image Generation
Electromyography (EMG)


Medical Diagnosis

Medical Image Segmentation
Electrocardiography (ECG) Analysis
Medical Diagnosis
Disease Prediction
X-Ray
Sleep Quality
Cancer Detection
Medical Image Registration
Medical Image Generation
Electromyography (EMG)

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