Preface About This Book Installing OCaml Introduction 1. Better Programming Through OCaml 1.1. The Past of OCaml 1.2. The Present of OCaml 1.3. Look to Your Future 1.4. A Brief History of CS 3110 1.5. Summary 2. The Basics of OCaml 2.1. The OCaml Toplevel 2.2. Compiling OCaml Programs 2.3. Expressions 2.4. Functions 2.5. Documentation 2.6. Printing 2.7. Debugging 2.8. Summary 2.9. Exercises OCaml
NumPyro Release We’re excited to announce the release of NumPyro, a NumPy-backed Pyro using JAX for automatic differentiation and JIT compilation, with over 100x speedup for HMC and NUTS! See the examples and documentation for more details. Pyro is a universal probabilistic programming language (PPL) written in Python and supported by PyTorch on the backend. Pyro enables flexible and expressive de
polysemy is a library for writing high-power, low-boilerplate domain specific languages. It allows you to separate your business logic from your implementation details. And in doing so, polysemy lets you turn your implementation code into reusable library code. It's like mtl but composes better, requires less boilerplate, and avoids the O(n^2) instances problem. It's like freer-simple but more pow
MLU-EXPLAIN Visual explanations of core machine learning concepts Machine Learning University (MLU) is an education initiative from Amazon designed to teach machine learning theory and practical application. As part of that goal, MLU-Explain exists to teach important machine learning concepts through visual essays in a fun, informative, and accessible manner. Neural Networks Learn about neural net
This article introduces readers to the mean-variance optimization of asset portfolios. The underlying formulas are implemented in Python. Market data has been downloaded from Google Finance. The case study is available here. Calculation of assets' weights, returns and covariances Our example starts with the calculation of vector of asset weights \(\mathbf{W}_{n \times 1}\), expected annual returns
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