unplush Simply follow the steps below. Step 1: Probability & Stats Variables & Linear Algebra (Tensors) Python, TensorFlow (Tensor operations) Data Visualization (Tabular Data) Step 2: Learn about some concept. Exploring Advanced Computer Architectures and Programming Techniques: 1. Performance Enhancement Techniques: Diving into concepts like Pipelining, Super-scalar Processors, SIMD Vectorization, and Caches for optimizing computer architectures. 2. Harnessing Parallel Processing: Understanding the power of Multicore Architectures, GPUs, and Data Access Optimization to leverage parallelism. 3. Parallel Programming Paradigms: Exploring Shared Memory Programming with OpenMP, Message-Passing with MPI, CUDA for GPUs, and the distributed computing framework, MapReduce. Step 3: Learn The ML Process — How to solve a problem using data and algorithms? What are the problems solvable by ML/AI? What cannot be solved? Data Types and State of the Art Models Tabular Data — Gradient B...
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