AI & Machine Learning
We develop smart, predictive AI solutions tailored to your business. Whether it's a vision system or a recommendation engine, our models are optimized for both accuracy and speed.
Work Process
Phase 1: Business Case & Dataset Analysis
• Define success KPIs (accuracy, latency,
precision)
• Assess dataset completeness and size
Phase 2: Data Processing
• Handle missing values, normalization, and
encoding
• Feature engineering using statistical analysis
Phase 3: Model Building
• Use CNNs, RNNs, SVMs, or Decision Trees
• Use pre-trained models like ResNet, YOLO, BERT
if needed
Phase 4: Evaluation & Improvement
• Confusion matrix, F1 score, ROC curve
• Grid search and cross-validation
Phase 5: Deployment
• Flask/Django REST APIs
• Dashboard or embedded firmware interface
Tools Used
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Industries Served
Visual Suggestions
• Dashboard mockups
• Neural network architecture diagram
We develop smart, predictive AI solutions tailored to your business. From computer vision to recommendation engines, our models are optimized for both accuracy and speed.
Services include:
• Predictive analytics
• Computer vision (face/object detection)
• Natural Language Processing (NLP)
• Time-series forecasting
• Recommendation systems
Phase 1: Business Case & Dataset Analysis
• Define KPIs (accuracy, latency, etc.)
• Assess dataset size and completeness
Phase 2: Data Processing
• Handle missing values, normalization
• Feature engineering with statistical methods
Phase 3: Model Building
• CNNs, RNNs, SVMs, Decision Trees
• Use of ResNet, YOLO, BERT where applicable
Phase 4: Evaluation & Improvement
• Metrics: F1, ROC, confusion matrix
• Grid search and cross-validation
Phase 5: Deployment
• Flask/Django REST APIs
• Dashboards or embedded firmware
• Python, Scikit-learn, PyTorch, TensorFlow
• OpenCV, HuggingFace, Keras
• Google Colab, Jupyter Notebook
• Smart Cities
• E-commerce & Retail
• Security & Surveillance
• Healthcare
• Dashboard mockups
• Neural network architecture diagrams