DagsHub

JULY 25, 2024

Source: Author Introduction Deep learning, a branch of machine learning inspired by biological neural networks, has become a key technique in artificial intelligence (AI) applications. Deep learning methods use multi-layer artificial neural networks to extract intricate patterns from large data sets.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

DataRobot

FEBRUARY 10, 2021

Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD by Jeremy Howard and Sylvain Gugger is a hands-on guide that helps people with little math background understand and use deep learning quickly. The following figure shows the Python code and how it led to data after November 2011.

Machine Learning 98

Machine Learning Machine Learning Data Scientist Deep Learning 98

AWS Machine Learning Blog

DECEMBER 14, 2023

This post is co-authored by Anatoly Khomenko, Machine Learning Engineer, and Abdenour Bezzouh, Chief Technology Officer at Talent.com. Established in 2011, Talent.com aggregates paid job listings from their clients and public job listings, and has created a unified, easily searchable platform.

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AWS Machine Learning Blog

OCTOBER 23, 2023

This post is co-authored by Anatoly Khomenko, Machine Learning Engineer, and Abdenour Bezzouh, Chief Technology Officer at Talent.com. Founded in 2011, Talent.com is one of the world’s largest sources of employment. It’s designed to significantly speed up deep learning model training. The model is replicated on every GPU.

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AWS Deep Learning Deep Learning Machine Learning 127

AWS Machine Learning Blog

MAY 10, 2023

Project Jupyter is a multi-stakeholder, open-source project that builds applications, open standards, and tools for data science, machine learning (ML), and computational science. In 2016, he co-created the Altair package for statistical visualization in Python.

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Mlearning.ai

JULY 30, 2023

Identifying important features using Python Introduction Features are the foundation on which every machine-learning model is built. Different machine-learning paradigms use different terminologies for features such as annotations, attributes, auxiliary information, etc. Hence, it is easy to import and use in Python.

Python 52

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Mlearning.ai

JUNE 5, 2023

Note : This blog is more biased towards python as it is the language most developers use to get started in computer vision. Python / C++ The programming language to compose our solution and make it work. Why Python? Easy to Use: Python is easy to read and write, which makes it suitable for beginners and experts alike.

Deep Learning 52

Deep Learning Deep Learning Python Machine Learning 52