Model Training & Optimisation
ClickMasters trains and optimises ML models for B2B companies across the USA, Europe, Canada, and Australia. Hyperparameter tuning with Optuna that systematically finds the model configuration your team's manual grid search missed. Feature selection that reduces overfitting and improves generalisation. Cross-validation that gives you honest performance estimates. And the MLOps infrastructure to retrain, evaluate, and deploy model updates without manual intervention.
Years Experience
Projects Delivered
Client Satisfaction
Support Available
The Most Common ML Model Problem: Overfitting
Overfitting is the most frequent reason a model that performs well in training underperforms in production. An overfit model has memorised the training data including its noise and idiosyncrasies rather than learning the underlying patterns that generalise to new data. Signs: training accuracy 95%, validation accuracy 72%. Causes: too many features relative to training examples, insufficient regularisation, data leakage (future information in training features), or a model that is too complex for the available data. Fixes: regularisation (L1/L2, dropout for neural networks), feature selection (remove low-information features), cross-validation (proper evaluation methodology), early stopping (stop training when validation metric stops improving), and ensemble methods (average multiple models reduces variance). ClickMasters diagnoses the specific cause before prescribing a fix.
Model Training & Optimisation Services We Deliver
ClickMasters operates as a full-stack model training & optimisation partner. Our team handles every layer of the software delivery lifecycle product strategy, UI/UX design, backend engineering, cloud infrastructure, QA, and ongoing support.
Hyperparameter Optimisation
Systematic hyperparameter search using Optuna (Bayesian optimisation). Search space definition, sampler selection (TPE, CMA-ES), pruning (MedianPruner reduces compute cost 50-80% vs grid search), hyperparameter importance analysis. Consistently finds better configurations in fewer trials than grid or random search.
Cross-Validation & Evaluation
Proper evaluation methodology for reliable performance estimates: k-fold CV (5/10-fold), stratified k-fold (preserve class balance for imbalanced data), time series CV (TimeSeriesSplit no leakage), nested CV (model selection + tuning), and calibration assessment (reliability diagrams).
Feature Selection & Importance
Reducing model complexity to improve generalisation and inference speed. Filter methods (variance, correlation), wrapper methods (Recursive Feature Elimination with CV), embedded methods (L1/Lasso), permutation importance, SHAP-based selection.
Model Distillation & Compression
Reducing model size and inference latency without proportional accuracy loss. Knowledge distillation (student-teacher), quantisation (float32 to int8 2-4x reduction), pruning (remove low-magnitude weights), ONNX export for cross-framework optimized inference.
AutoML Pipeline
Automated model selection and hyperparameter tuning: FLAML (Microsoft fast, resource-aware), AutoGluon (Amazon strong ensembling), H2O AutoML (enterprise-grade), PyCaret (low-code, compares 15+ algorithms). Establishes strong baseline quickly before specialist optimisation.
Why Companies Choose ClickMasters
Learns from previous trials, prunes unpromising runs 50-80% compute reduction
Basic: Grid search (exhaustive, blind) or random search (uninformed)
Amber callout with specific signs, causes, fixes
Basic: No overfitting detection or resolution
Time series CV, nested CV, calibration assessment never random splits for time-sensitive data
Basic: Random splits (optimistic, leaky metrics)
Student-teacher + quantisation + ONNX 5-10x smaller, 2-5x faster
Basic: Model as-is (overly large, slow inference)
Systematic review of every feature for leakage potential
Basic: Leakage missed until model fails in production
Our Process
Our Model Training & Optimisation Process
A proven methodology that transforms your vision into reality
Model Audit & Evaluation Review
Current performance assessment, overfitting diagnosis (training vs validation gap), data leakage review, evaluation methodology audit, improvement opportunity identification. Deliverable: Model Audit Report with Improvement Plan.
Hyperparameter Optimisation
Search space definition, sampler selection (TPE/CMA-ES), pruning configuration (MedianPruner), Optuna study execution (100-500 trials), hyperparameter importance analysis, retrain with optimal config. Deliverable: Optimised Model + Hyperparameter Importance Report.
Feature Engineering & Selection
Feature importance analysis, Recursive Feature Elimination with CV, SHAP-based selection, L1 regularisation, new feature engineering if gaps identified. Deliverable: Reduced Feature Set + Performance Comparison.
Model Distillation (Optional)
Teacher model (current/large) → Student model (smaller architecture) training, quantisation (int8/float16), ONNX export, latency benchmarking. Deliverable: Distilled Model + Latency Report.
MLOps Retraining Pipeline
Automated retraining triggers (schedule or drift), evaluation gate (performance must not regress vs current), model registry promotion workflow, deployment CI/CD. Deliverable: Retraining Pipeline + Dashboard.
Technology Stack
Modern tools we use to build scalable, secure applications.
Languages & Frameworks
Data Processing
Infrastructure
Industry-Specific Expertise
Deep expertise across various sectors with tailored solutions
Overfitting Diagnosis
Hyperparameter Tuning
Model Distillation
MLOps Retraining
Pricing
Model Training & Optimisation Development Pricing
Transparent pricing tailored to your business needs
Model Audit & Evaluation Review
Perfect for businesses that need model audit & evaluation review solutions
one-time project range
Package Includes
- Timeline: 1 - 2 weeks
- Best For: Evaluation methodology review, overfitting diagnosis, improvement plan
- Budget Range: 3,000 - 7,000 AUD
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
Hyperparameter Optimisation
Perfect for businesses that need hyperparameter optimisation solutions
one-time project range
Package Includes
- Timeline: 2 - 3 weeks
- Best For: Optuna search, search space design, result analysis, retrained model
- Budget Range: 5,000 - 15,000 AUD
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
Cross-Validation Framework
Perfect for businesses that need cross-validation framework solutions
one-time project range
Package Includes
- Timeline: 1 - 2 weeks
- Best For: CV strategy, stratification, time series CV, calibration assessment
- Budget Range: 4,000 - 10,000 AUD
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
Feature Engineering & Selection
Perfect for businesses that need feature engineering & selection solutions
one-time project range
Package Includes
- Timeline: 2 - 4 weeks
- Best For: Feature importance, RFE, SHAP selection, dimensionality reduction
- Budget Range: 6,000 - 18,000 AUD
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
Model Distillation / Compression
Perfect for businesses that need model distillation / compression solutions
one-time project range
Package Includes
- Timeline: 2 - 5 weeks
- Best For: Student-teacher distillation, quantisation, ONNX export, latency benchmark
- Budget Range: 8,000 - 22,000 AUD
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
Full Model Optimisation
Perfect for businesses that need full model optimisation solutions
one-time project range
Package Includes
- Timeline: 4 - 8 weeks
- Best For: All above: evaluation + tuning + feature + compression + deployment
- Budget Range: 15,000 - 45,000 AUD
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
* All prices are estimates and may vary based on requirements.
CEO Vision
To build scalable, intelligent custom software development solutions that empower businesses to grow, automate, and transform in a digital-first world.
We are not building software. We are architecting the infrastructure of tomorrow systems that think, adapt, and grow alongside the businesses they power. Our mission is to make cutting-edge technology accessible to every ambitious team on the planet.
Amjad Khan
CEO
12+
Years
300+
Projects
98%
Retention
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