Deep Learning & Neural Foundation Mechanics

Tensors, backpropagation, modern activations, and optimization algorithms.

2 weeks · wk 3–4Core / deep pace5 topics15 Interview Questions

Why this pace:To diagnose model failure modes, optimize batching, and customize loss functions, you must understand tensor computation graphs, gradient flows, and loss dynamics.

SEC FOCUS

Unnormalized inputs or exploding gradients can produce NaN outputs that silently corrupt model checkpoints during training.

Topics & Action Items (5)

PyTorch Tensors, Autograd & Computation Graphs

5 hrs

Modern Architectures: LayerNorm, RMSNorm & SwiGLU

4 hrs

Optimization: AdamW, Weight Decay & Schedulers

4 hrs

Precision Formats: FP32, FP16, BF16 & FP8

4 hrs

Loss Functions, Cross-Entropy & Perplexity

3 hrs

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