BSDA5013
10 Internal Entities Declared
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208 - PyTorch Fundamentals for Deep Learning PracticeAccess ->
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209 - Data Loading & Pipelines- Dataset, DataLoader, TransformationsAccess ->
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210 - Pandas for Deep Learning- DataFrames, Series, and GPU-Accelerated Data ProcessingAccess ->
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211 - Training & Debugging- Gradient Clipping, LR Scheduling, NaN DetectionAccess ->
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212 - Distributed Training- DDP, Gradient Accumulation, and Mixed PrecisionAccess ->
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213 - Mixed Precision Training- FP16-FP32, GradScaler, and AMPAccess ->
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214 - Profiling & Optimization- PyTorch Profiler, FLOPs, MemoryAccess ->
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215 - Model Deployment- ONNX, TensorRT, Quantization, and PruningAccess ->
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216 - Experiment Tracking- MLflow, W&B, Metrics Logging, Hyperparameter SweepsAccess ->
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217 - NLP Projects- Tokenization, Fine-Tuning, Text Classification, Seq2SeqAccess ->