EPOCH_2040 • BUILD_AUTONOMOUS_INTELLIGENCE
NEURAL_INTELLIGENCE_FRAMEWORK • NODE_ACTIVE • ALL_AGENTS_ONLINE
// AUTONOMOUS_ML_PROTOCOL • INITIALIZING

AUTO
NOMOUS
MACHINE LEARNING

UPLOAD_DATASET • DEFINE_GOAL • EXECUTE
140+ NEURAL AGENTS BUILD YOUR ML MODEL IN <60 SECONDS
NO_CODE • NO_CONFIG • PRODUCTION_READY

INITIALIZE_SYSTEM ACCESS_PROTOCOL
140+
AI_AGENTS
9
ENDPOINTS
5.5K
LOC
<50ms
LATENCY
22
MODULES
EXECUTION_FLOW • PIPELINE_SEQUENCE
IN
STEP_01
INGEST
CSV upload
Auto-profile
Zero config
NL
STEP_02
PARSE
Natural lang
Goal decode
Task tree
AG
STEP_03
EXECUTE
140+ agents
Parallel run
AutoML
ML
STEP_04
TRAIN
XGBoost
LightGBM
Neural nets
OUT
STEP_05
DELIVER
Model file
Metrics
HTML report
AGENT_REGISTRY • 140+ UNITS ONLINE
CORE_PIPELINE
11 UNITS • ACTIVE
NLP_SUITE
10 UNITS • ACTIVE
VISION_CORE
9 UNITS • ACTIVE
AUTOML_ENGINE
5 UNITS • ACTIVE
MLOPS_MONITOR
5 UNITS • ACTIVE
RAG_PROTOCOL
4 UNITS • ACTIVE
TIME_SERIES
5 UNITS • ACTIVE
REINFORCE_LEARN
6 UNITS • ACTIVE
GRAPH_NEURAL
6 UNITS • ACTIVE
USE_CASES • DOMAIN_COVERAGE
🏦
FINANCE
Credit scoring. Fraud detect. Churn prediction. Risk modeling.
🏥
HEALTHCARE
Disease predict. Readmission risk. Treatment optimization.
🛒
E-COMMERCE
Recommendations. Price optimization. Demand forecasting.
📈
ANALYTICS
Revenue forecast. Segmentation. Trend analysis.
SYSTEM_MODULES • CAPABILITIES
BACKEND
FASTAPI CORE
Async REST. JWT auth. Swagger. 9 endpoints. Real-time job streams.
AUTOML
ALGO SELECTOR
XGBoost. LightGBM. RF. Neural. Auto-benchmark. Best model wins.
REPORTS
HTML DISPATCH
Full reports. SHAP explainability. Feature maps. Downloadable.
SECURITY
JWT + RBAC
bcrypt hashing. Role-based. Token expiry. Zero-trust design.
DEVOPS
CI/CD PIPELINE
Docker. GitHub Actions. Auto-test. HuggingFace deploy. Live.
TRACKING
MLFLOW CORE
Experiment log. Model versions. Run compare. Artifact store.
EXPLAINABILITY
SHAP ANALYSIS
Every prediction explained. Feature contributions. Bias detect.
DEPLOYED
HF LIVE NOW
keshav1838-veda-ml-platform.hf.space — live API. Free forever.
API_HANDSHAKE • LIVE_INTERFACE
VEDA_TERMINAL • NEURAL_INTERFACE • AUTHENTICATED • v2.0.0
// STEP_01: AUTHENTICATE • OBTAIN_ACCESS_TOKEN
curl -X POST https://keshav1838-veda-ml-platform.hf.space/auth/login \
    -H "Content-Type: application/json" \
    -d '{"username":"admin","password":"admin123"}'
→ {"access_token": "eyJhbGci...", "token_type": "bearer"}

// STEP_02: SUBMIT_WORKFLOW • INITIATE_AGENT_SWARM
curl -X POST https://keshav1838-veda-ml-platform.hf.space/workflows \
    -H "Authorization: Bearer $TOKEN" \
    -d '{"dataset_path":"data.csv","goal":"predict churn"}'
→ {"job_id": "a3f2c1d4-8b9e...", "status": "submitted"}

// STEP_03: RETRIEVE_RESULT • MISSION_COMPLETE
curl https://keshav1838-veda-ml-platform.hf.space/workflows/$JOB_ID
→ {"status": "completed", "model": "xgboost", "accuracy": 0.891, "f1": 0.874}
// INITIATE_SEQUENCE • AWAITING_OPERATOR_CONFIRMATION
DEPLOY
INTELLIGENCE

FREE_TO_USE • NO_SIGNUP_REQUIRED
FIRST_MODEL_ONLINE_IN_UNDER_60_SECONDS
NO_ML_EXPERTISE_NEEDED • JUST_UPLOAD_AND_DESCRIBE

ACCESS_API VIEW_SOURCE