k-dense-ai

4★

@k-dense-ai

Run molecular machine learning workflows with DeepChem for property prediction, featurization, and benchmarked datasets.

4★

@k-dense-ai

Build Bayesian models with PyMC using hierarchical models, MCMC, variational inference, and posterior checks.

3★

@k-dense-ai

Orchestrate scalable PyTorch training with Lightning modules, trainers, callbacks, and distributed execution.

3★

@k-dense-ai

Build, simulate, transpile, and execute quantum circuits with Qiskit and IBM Quantum Runtime.

2★

@k-dense-ai

Perform cheminformatics analysis with RDKit for molecular parsing, descriptors, fingerprints, reactions, and similarity.

3★

@k-dense-ai

Run standard single-cell RNA-seq analysis with Scanpy for QC, clustering, visualization, and differential expression.

2★

@k-dense-ai

Model single-cell omics data with scvi-tools for batch correction, transfer learning, and multimodal integration.

3★

@k-dense-ai

Train reinforcement learning agents with Stable-Baselines3 using PPO, SAC, DQN, TD3, and related algorithms.

4★

@k-dense-ai

Build graph neural network workflows with PyTorch Geometric for node, link, and graph prediction.

3★

@k-dense-ai

Work with Hugging Face Transformers for model loading, pipeline inference, generation, and trainer fine-tuning.