Predict malignancy in cancer tumors with your own neural network
https://towardsdatascience.com/predict-malignancy-in-breast-cancer-tumors-with-your-own-neural-network-and-the-wisconsin-dataset-76271a05e941?source=collection_home---4------0---------------------
https://towardsdatascience.com/predict-malignancy-in-breast-cancer-tumors-with-your-own-neural-network-and-the-wisconsin-dataset-76271a05e941?source=collection_home---4------0---------------------
Towards Data Science
Predict malignancy in cancer tumors with your own neural network
Predict malignancy in breast cancer tumors using a neural network you code from scratch in Python and the Wisconsin Cancer Dataset
The Ancient Secrets of Computer Vision University of Washington.
Free course
This class is a general introduction to computer vision. It covers standard techniques in image processing like filtering, edge detection, stereo, flow, etc. , as well as newer, machine-learning based computer vision.
https://pjreddie.com/courses/computer-vision/
Free course
This class is a general introduction to computer vision. It covers standard techniques in image processing like filtering, edge detection, stereo, flow, etc. , as well as newer, machine-learning based computer vision.
https://pjreddie.com/courses/computer-vision/
Pjreddie
The Ancient Secrets of Computer Vision
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Introduction to gradient boosting on decision trees with Catboost
Today I would like to share my experience with open source machine learning library, based on gradient boosting on decision trees, developed by Russian search engine company — Yandex.
https://towardsdatascience.com/introduction-to-gradient-boosting-on-decision-trees-with-catboost-d511a9ccbd14
Today I would like to share my experience with open source machine learning library, based on gradient boosting on decision trees, developed by Russian search engine company — Yandex.
https://towardsdatascience.com/introduction-to-gradient-boosting-on-decision-trees-with-catboost-d511a9ccbd14
Medium
Introduction to gradient boosting on decision trees with Catboost
Today I would like to share my experience with open source machine learning library, based on gradient boosting on decision trees…
Forwarded from Artificial Intelligence
What To Optimize for? Loss Function Cheat Sheet
https://medium.com/@urimerhav/what-to-optimize-for-loss-function-cheat-sheet-5fc8b1339939
https://medium.com/@urimerhav/what-to-optimize-for-loss-function-cheat-sheet-5fc8b1339939
Medium
What To Optimize for? Loss Function Cheat Sheet
Some tips in finding the right target for optimization, and how to figure it out for your use case
Box Convolution Layer for ConvNets
This is a PyTorch implementation of the box convolution layer as introduced in the 2018 NeurIPS paper:
https://github.com/shrubb/box-convolutions
This is a PyTorch implementation of the box convolution layer as introduced in the 2018 NeurIPS paper:
https://github.com/shrubb/box-convolutions
GitHub
GitHub - shrubb/box-convolutions: PyTorch code for the "Deep Neural Networks with Box Convolutions" paper
PyTorch code for the "Deep Neural Networks with Box Convolutions" paper - shrubb/box-convolutions
Image Segmentation using Python’s scikit-image module
https://towardsdatascience.com/image-segmentation-using-pythons-scikit-image-module-533a61ecc980
https://towardsdatascience.com/image-segmentation-using-pythons-scikit-image-module-533a61ecc980
Towards Data Science
Image Segmentation using Python's scikit-image module | Towards Data Science
An overview of the scikit-image library's image segmentation methods.
Forwarded from Artificial Intelligence
How Should Self-Driving Cars Choose Who Not to Kill?
https://medium.com/@MORGANMEAKER/how-should-self-driving-cars-choose-who-not-to-kill-442f2a5a1b59?source=topic_page---------------------------20
https://medium.com/@MORGANMEAKER/how-should-self-driving-cars-choose-who-not-to-kill-442f2a5a1b59?source=topic_page---------------------------20
Medium
How Should Self-Driving Cars Choose Who Not to Kill?
A popular MIT quiz asked ordinary people to make ethical judgments for machines
Introducing PlaNet: A Deep Planning Network for Reinforcement Learning
https://ai.googleblog.com/2019/02/introducing-planet-deep-planning.html
https://ai.googleblog.com/2019/02/introducing-planet-deep-planning.html
blog.research.google
Introducing PlaNet: A Deep Planning Network for Reinforcement Learning
GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/albertpumarola/GANimation
https://github.com/albertpumarola/GANimation
GitHub
GitHub - albertpumarola/GANimation: GANimation: Anatomically-aware Facial Animation from a Single Image (ECCV'18 Oral) [PyTorch]
GANimation: Anatomically-aware Facial Animation from a Single Image (ECCV'18 Oral) [PyTorch] - albertpumarola/GANimation
DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning
https://www.nature.com/articles/s41598-018-38343-3
https://www.nature.com/articles/s41598-018-38343-3
Nature
DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning
Scientific Reports - DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning
On the Path to Cryogenic Control of Quantum Processors
http://ai.googleblog.com/2019/02/on-path-to-cryogenic-control-of-quantum.html
http://ai.googleblog.com/2019/02/on-path-to-cryogenic-control-of-quantum.html
research.google
On the Path to Cryogenic Control of Quantum Processors
Posted by Joseph Bardin, Visiting Faculty Researcher and Erik Lucero, Staff Research Scientist and Hardware Lead, Google AI Quantum Team Building a...
HandCrafting an Artificial Neural Network
In this article, I have implemented a fully vectorized code for Artificial Neural Network with Dropout and L2 Regularization.
https://towardsdatascience.com/handcrafting-an-artificial-neural-network-e0b663e88a53
In this article, I have implemented a fully vectorized code for Artificial Neural Network with Dropout and L2 Regularization.
https://towardsdatascience.com/handcrafting-an-artificial-neural-network-e0b663e88a53
Medium
HandCrafting an Artificial Neural Network
Having learnt the making and working of a neural network, it is very important to implement the code for better understanding.
1albon_c_machine_learning_with_p.pdf
3.4 MB
Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning
Getting Started with Reinforcement Learning and Open AI Gym
https://towardsdatascience.com/getting-started-with-reinforcement-learning-and-open-ai-gym-c289aca874f
https://towardsdatascience.com/getting-started-with-reinforcement-learning-and-open-ai-gym-c289aca874f
Medium
Getting Started with Reinforcement Learning and Open AI Gym
Solving the Mountain Car environment using Q-learning.
Learning to Generalize from Sparse and Underspecified Rewards
http://ai.googleblog.com/2019/02/learning-to-generalize-from-sparse-and.html
http://ai.googleblog.com/2019/02/learning-to-generalize-from-sparse-and.html
Googleblog
Learning to Generalize from Sparse and Underspecified Rewards