Category
Machine Learning
Deep dives into ML algorithms, models, and applications
// 12 articles filed
// FIG. CAT-MACH
PristrenPristrenDeep dives into ML algorithms, models, and applications
// 12 articles filed
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Decision trees overfit easily. Random forests fix this by averaging many trees. XGBoost pushes further with gradient boosting. Here is when tree methods beat neural networks.
Mahmudul Haque Qudrati
CEO & ML Engineer
Data quantity requirements, labeling strategies, augmentation techniques, the data flywheel, and how production models generate their own training data.
Mahmudul Haque Qudrati
CEO & ML Engineer
Why models degrade, what to monitor, detecting drift with statistical tests, automated retraining triggers, and tools like Evidently AI and Arize.
Mahmudul Haque Qudrati
CEO & ML Engineer
How semantic search works, embedding-based architecture, pgvector vs ChromaDB, hybrid search with BM25, and cross-encoder re-ranking for better results.
Mahmudul Haque Qudrati
CEO & ML Engineer
Accuracy is misleading on imbalanced datasets. Here is when to use precision, recall, F1, AUC-ROC, MAE, RMSE, and how to choose the right metric for your problem.
Mahmudul Haque Qudrati
CEO & ML Engineer
REST APIs, batch inference, streaming, edge deployment, model serving frameworks, and canary deployments for safely rolling out new model versions.
Mahmudul Haque Qudrati
CEO & ML Engineer
Using pretrained models for classification, detection, OCR, and segmentation. APIs vs local inference. When to fine-tune vs use a multimodal LLM. CLIP for image search.
Mahmudul Haque Qudrati
CEO & ML Engineer
CNNs use convolutions to detect local patterns in images. Pooling downsamples. ResNet residual connections solve vanishing gradients. Here is when to train from scratch vs. use a pretrained model.
Mahmudul Haque Qudrati
CEO & ML Engineer
GPT's autoregressive, decoder-only design enables text generation at scale. Here is how it actually works -- from pretraining data to emergent capabilities to GPT-4o.
Mahmudul Haque Qudrati
CEO & ML Engineer
BERT introduced bidirectional context to NLP in 2018. Here is what that means, how it differs from GPT, and when to reach for it over a modern LLM API.
Mahmudul Haque Qudrati
CEO & ML Engineer
Anomaly detection finds rare events without labeled examples. Here is how Isolation Forest, One-Class SVM, and Autoencoders work -- and why accuracy is the wrong metric.
Mahmudul Haque Qudrati
CEO & ML Engineer
Supervised learning is the most widely used ML paradigm. Here is exactly how the train-measure-adjust loop works, where labels come from, and when the approach breaks down.
Mahmudul Haque Qudrati
CEO & ML Engineer
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