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Category Archives: Machine Learning
The Flax Neural Network Library
I came across two interesting, related, Python libraries recently: JAX and Flax. JAX (“just after execution”) is sort of an enhanced NumPy (numerical Python) library. JAX adds support for numeric arrays on GPU and TPU hardware, and automatic gradient calculation. … Continue reading
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Matrix Inverse From Scratch Using Python
Computing the inverse of a matrix is a fundamental algorithm for machine learning and numerical programming. On a recent flight to a conference, just for hoots (and for programming exercise) I decided to implement a matrix inverse function from scratch … Continue reading
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JavaScript and the SapirWhorf Hypothesis
The SapirWhorf hypothesis loosely states that the structure of a spoken language affects its the way its speakers see and understand the world. This makes intuitive sense — a tribesman from a primitive country there the language doesn’t have words … Continue reading
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What Are Progressive Neural Networks for Transfer Learning?
Deep neural networks have made incredible progress in tabular data classification and regression, natural language processing, and image recognition. But one of the weaknesses of DNNs is that they are very problemspecific. A DNN trained to play chess doesn’t do … Continue reading
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Matrix Determinant from Scratch Using Python
A few days ago I was exploring the ideas behind implementing matrix inversion from scratch using Python. There are dozens of matrix inversion algorithms but the one I usually use involves decomposing the source matrix into two other matrices. And … Continue reading
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Researchers Explore QuantumInspired Optimization on the Pure AI Web Site
I contributed to an article titled “Researchers Explore QuantumInspired Optimization” in the December 2021 edition of the Pure AI web site. See https://pureai.com/articles/2021/12/01/quantuminspiredoptimization.aspx. Quantuminspired optimization starts with a standard algorithm, such as particle swarm optimization or simulated annealing, and modifies … Continue reading
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Matrix Decomposition Using Python
One of the fundamental algorithms in machine learning and numerical programming is matrix decomposition. The idea is to break a source matrix M into two matrices A and B so that A * B = M. Matrix decomposition doesn’t have … Continue reading
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The Traveling Salesman Problem Using Quantum Inspired Annealing In C#
The Traveling Salesman Problem (TSP) is a standard combinatorial optimization problem. The goal is to find the best route that visits all cities, where best route usually means shortest distance. Simulated annealing is one way to solve TSP. Quantum inspired … Continue reading
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Knapsack Problem Using Simulated Annealing Example
A combinatorial optimization problem is one where the goal is to find the optimal ordering / permutation of a set of discrete items. A standard example is called the knapsack problem. It’s best explained by example. Here’s an example I … Continue reading
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Simulated Annealing Optimization Using C# or Python in Visual Studio Magazine
I wrote an article titled “Simulated Annealing Optimization Using C# or Python” in the December 2021 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2021/12/01/travelingsalesman.aspx. The goal of a combinatorial optimization problem is to find the best ordering of a set … Continue reading
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