Answer (1 of 13): 1. A simple course in neural networks should help (Geoff Hintons course on coursera) 2. Gradient Descent/Stochastic Gradient Descent 3. Logistic Regression 4. Ability to code in a standard programming language (Python, Java, C++ etc) 5. An understanding of probability, linear al...
Accelerated Learning cuDNN provides kernels, targeting Tensor Cores, to deliver best available performance on compute-bound operations. It offers heuristics for choosing the right kernel for a given problem size. Expressive Op Graph API The user defines computations as a graph of operations on tensors. The cuDNN library has both a direct C API and an open-source C++ frontend for convenience. Most
Machine Learning video segments by topic - Professor Yaser Abu-Mostafa Aggregation Overview of ensemble learning (boosting, blending, before and after the fact) Bayesian Learning Validity of the Bayesian approach (prior, posterior, unknown versus probabilistic) Bias-Variance Tradeoff Basic derivation (overfit and underfit, approximation-generalization tradeoff) Example (sinusoidal target function)
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