Computational Mindset

Algorithms, AI, Applied Mathematics, Operations Research, Quantum Programming and other topics concerning the computing, that is the third pillar of science.

[Computational Mindset @Computational_M]

Published on https://t.co/mlmLjCKRv5 a post showing the calculation of an integral of a function on a GPU with CUDA toolkit using the trapezoid rule.

https://t.co/BTkzjz2ryP

[Computational Mindset @Computational_M]

Published on https://t.co/mlmLjCKRv5 a post showing the calculation of discrete partial prime derivatives on GPU with CUDA toolkit.

https://t.co/GhD9jtOxr1

[Computational Mindset @Computational_M]

Published on https://t.co/mlmLjCKRv5 a post showing the calculation of discrete prime derivative on GPU with CUDA toolkit.

https://t.co/uzN62aG51A

[Computational Mindset @Computational_M]

Example of rips complex that is a way of forming a topological space from distances in a set of points.

[Computational Mindset @Computational_M]

This post is the first in the series of posts on reverse engineering and shows how the five arithmetic operations are compiled in assembly by C++ and Rust compilers on Linux with x86_64 architecture.

https://t.co/HGMvNtqwOl

[Paul Skrzypczyk @PaulSkrzypczyk]

There was an exciting package waiting for me at work this morning - a physical copy of my textbook! Thank you @IOPPublishing! It is quite surreal to see it in the flesh. It took a lot longer to write than we originally planned, but I'm glad that we got it finished, and to see..

[PyQuant News 🐍 @pyquantnews]

The harsh truth about being a quant:

You have to read a lot.

The 4 books every aspiring quant needs on their bookshelf:

[Computational Mindset @Computational_M]

Sul canale YouTube di Computational Mindset è stato pubblicato il terzo video sulla computazione quantistica dal titolo "Dal processo classico al processo quantistico. Dal bit al qubit":
https://t.co/Bn20GscRfC

#computazionequantistica #quantum #quantumcomputing

[Computational Mindset @Computational_M]

Sul canale YouTube di https://t.co/TQSSfGqeg5 è stato pubblicato il secondo video sulla computazione quantistica.

Qui il link al secondo video dal titolo "Fisica quantistica vs fisica classica":
https://t.co/TCyaVAzGJ6

#computazionequantistica #quantum #quantumcomputing

[Computational Mindset @Computational_M]

Sul canale YouTube di Computational Mindset è stato pubblicato il primo video di una serie di 14 video sulla computazione quantistica.

Qui il primo video dal titolo "Entropia e computer quantistici":
https://t.co/lEOxi0CftV

#computazionequantistica #quantum #quantumcomputing

[Computational Mindset @Computational_M]

Parametric curve in space fitting with TensorFlow

The topic of this post is the fitting of a parametric curve on a 3-D reference system Oxyz with parameter t.

Click here for more:
https://t.co/Db3VQz0lSg

#neuralnetworks #deeplearning #artificialintelligence #ai

[Computational Mindset @Computational_M]

One-variable real-valued function fitting with PyTorch

The topic of this post is the fitting of a continuous and limited real-valued function defined in a closed interval.

Click here for more:
https://t.co/OzFwTpyW9o

#neuralnetworks #deeplearning #artificialintelligence #ai

[Computational Mindset @Computational_M]

Parametric curve on plane fitting with TensorFlow

The topic of this post is the fitting of a parametric curve on a Cartesian reference system Oxy.

Click here for more:
https://t.co/Hn01CUrSE1

#neuralnetworks #deeplearning #artificialintelligence #ai #computationalmindset

[Computational Mindset @Computational_M]

One-variable real-valued function fitting with PyTorch

This post is part of a series of posts on the fitting of mathematical objects (functions, curves and surfaces) through a MLP (Multi-Layer Perceptron).

Click here for more:
https://t.co/OzFwTpyW9o

#neuralnetworks #ai

[Computational Mindset @Computational_M]

One-variable real-valued function fitting with TensorFlow

This post is part of a series of posts on the fitting of mathematical objects through a MLP neural network.

Click here for more:
https://t.co/bUom07F3ZI

#neuralnetworks #deeplearning #artificialintelligence #ai

[Computational Mindset @Computational_M]

Common tools for function fitting

This post describes the use of a set of common tools written in Python to generate and display synthetic datasets.

Click here for more:
https://t.co/JuYjy7VzbN

#machinelearning #deeplearning #artificialintelligence #ai #computationalmindset

[Computational Mindset @Computational_M]

Fitting functions with PyCaret

This post deals with the approximation of real mathematical functions to one or more real variables.

Click here for more:
https://t.co/qVlTElIOmZ

#machinelearning #deeplearning #artificialintelligence #ai #computationalmindset

[Computational Mindset @Computational_M]

NOT and C-NOT quantum gates

The operators of traditional high-level programming languages are translated by the compilers into short sequences of machine language instructions.

Click here for more:
https://t.co/YI27KitUR1

#quantumcomputing #quantumprogramming #ai

[Computational Mindset @Computational_M]

Pruning of neural networks with TensorFlow

The purpose of pruning of the weights based on magnitude is to gradually zero out the less significant weights of the model during the training phase.

Click here for more:
https://t.co/fW1zoM0qmY

#neuralnetworks #deeplearning #ai

[Computational Mindset @Computational_M]

Ordinary differential equation solvers in Julia

All the various code fragments described in this post require Julia version 1.5.3 and the following packages: DifferentialEquations, StaticArrays and Plots.

Click here for more:
https://t.co/CcqK4o2TJd

#neuralnetworks #ai