presentations by JuliaCon

Presentations for JuliaCon

updated at May 16, 2021, 12:03 a.m.

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ROCAnalysis.jl by davidavdav

Receiver Operating Characteristics and functions for evaluation probabilistic binary classifiers

updated at June 4, 2023, 2:11 a.m.

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breze by breze-no-salt

Breze with all the stuff.

updated at Aug. 23, 2023, 9:04 p.m.

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BigDataAnalytics_INFOH515 by Yannael

Material for the Big Data Analytics exercise classes - INFOH515 - Big Data : Distributed Data Management and Scalable Analytics - Université Libre de Bruxelles

updated at Nov. 23, 2023, 9:45 p.m.

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Data_visualization by Shanky-21

None

updated at Feb. 25, 2024, 3:08 a.m.

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Flight_Fare_Prediction by ShivamChoudhary17

Flight_Fare_Prediction

updated at April 6, 2024, 7:59 p.m.

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minigrad by kennysong

A minimal implementation of autograd (in pure Python) 🍰

updated at April 14, 2024, 6:24 p.m.

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neon_course by NervanaSystems

neon tutorials

updated at April 28, 2024, 3:50 p.m.

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Heart_Disease by ShivamChoudhary17

Machine Learning

updated at April 29, 2024, 11:22 a.m.

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Machine_learning by Shanky-21

You can Learn Basic Machine learning Techniques from here

updated at May 3, 2024, 7:46 a.m.

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gan by tensorflow

Tooling for GANs in TensorFlow

updated at May 10, 2024, 4:45 a.m.

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notebooks by ogrisel

Some sample IPython notebooks for scikit-learn

updated at May 10, 2024, 11:13 a.m.

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rep by yandex

Machine Learning toolbox for Humans

updated at May 14, 2024, 8:58 p.m.

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Knet.jl by denizyuret

Koç University deep learning framework.

updated at May 17, 2024, 5:10 p.m.

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GaussianProcesses.jl by STOR-i

A Julia package for Gaussian Processes

updated at May 17, 2024, 7:27 p.m.

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tensorwatch by Microsoft

Debugging, monitoring and visualization for Python Machine Learning and Data Science

updated at May 20, 2024, 11:45 a.m.

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ml-workspace by ml-tooling

🛠 All-in-one web-based IDE specialized for machine learning and data science.

updated at May 20, 2024, 11:45 a.m.

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the-elements-of-statistical-learning by maitbayev

My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman

updated at May 21, 2024, 6:29 a.m.

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shapash by MAIF

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

updated at May 21, 2024, 10:06 a.m.

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AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics by Western-OC2-Lab

Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

updated at May 21, 2024, 11:52 a.m.

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