Artificial Intelligence solutions
Our proficiency in innovative frameworks and tools, solid and efficient hands-on experience, ready-made solutions based on Deep Neural Networks together with the contemporary tensor processing acceleration makes us the superior choice on your digital transformation way.
Why Innovative Future?
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
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 Relearning the models on a new (not outdated) data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
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
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)
What We Guarantee
Artificial Intelligence Services
Machine and Deep Learning
Data Science
Business Intelligence
Data Mining and Analytics
Big Data
Machine Learning Solutions
Superior data extraction accuracy
Deep Neural Networks algorithms
Tensor processing acceleration
Ready-made solutions
Quick ML-model training time
Professional Team
Expert and Invaluable Knowledge
Solid and Efficient Hands-On Experience
High-Quality Outputs and Deliverables
Focus on Customer Experience
Never Miss a Beat
Have a question?
Innovative Future, Inc.
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