Boosting Machine Learning Tutorial | Gradient Boosting, XGBoost
https://www.youtube.com/watch?v=kho6oANGu_A
https://www.youtube.com/watch?v=kho6oANGu_A
YouTube
Boosting Machine Learning Tutorial | Adaptive Boosting, Gradient Boosting, XGBoost | Edureka
** Machine Learning Certification Training using Python: https://www.edureka.co/python **
This Edureka session will help you understand all about Boosting Machine Learning and boosting algorithms and how they can be implemented to increase the efficiency…
This Edureka session will help you understand all about Boosting Machine Learning and boosting algorithms and how they can be implemented to increase the efficiency…
Data Augmentation Strategies for Object Detection
Article: https://arxiv.org/abs/1906.11172
GIthub: https://github.com/tensorflow/tpu/tree/master/models/official/detection
Article: https://arxiv.org/abs/1906.11172
GIthub: https://github.com/tensorflow/tpu/tree/master/models/official/detection
arXiv.org
Learning Data Augmentation Strategies for Object Detection
Data augmentation is a critical component of training deep learning models. Although data augmentation has been shown to significantly improve image classification, its potential has not been...
Predicting Bus Delays with Machine Learning
http://ai.googleblog.com/2019/06/predicting-bus-delays-with-machine.html
http://ai.googleblog.com/2019/06/predicting-bus-delays-with-machine.html
research.google
Predicting Bus Delays with Machine Learning
Posted by Alex Fabrikant, Research Scientist, Google Research Hundreds of millions of people across the world rely on public transit for their da...
Announcing the YouTube-8M Segments Dataset
http://ai.googleblog.com/2019/06/announcing-youtube-8m-segments-dataset.html
http://ai.googleblog.com/2019/06/announcing-youtube-8m-segments-dataset.html
blog.research.google
Announcing the YouTube-8M Segments Dataset
How to Develop a GAN for Generating Handwritten Digits
https://machinelearningmastery.com/how-to-develop-a-generative-adversarial-network-for-an-mnist-handwritten-digits-from-scratch-in-keras/
https://machinelearningmastery.com/how-to-develop-a-generative-adversarial-network-for-an-mnist-handwritten-digits-from-scratch-in-keras/
FREE COURSE Intro to TensorFlow for Deep Learning
This course is a practical approach to deep learning for software developers
https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187
This course is a practical approach to deep learning for software developers
https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187
Udacity
TensorFlow for Deep Learning Training Course | Udacity
Learn online and advance your career with courses in programming, data science, artificial intelligence, digital marketing, and more. Gain in-demand technical skills. Join today!
How to Develop a GAN for Generating Small Color Photographs of Objects
https://machinelearningmastery.com/how-to-develop-a-generative-adversarial-network-for-a-cifar-10-small-object-photographs-from-scratch/
https://machinelearningmastery.com/how-to-develop-a-generative-adversarial-network-for-a-cifar-10-small-object-photographs-from-scratch/
МегаФон запускает «Фабрику микросервисов» - «завод» по разработке и внедрению новых технологических решений на базе микросервисной архитектуры.
Фабрика базируется в Нижнем Новгороде и будет работать по гибким методологиям Agile, по принципу кросс-функциональных DevOps команд.
В распоряжении «фабрикантов» будут самые передовые инструменты разработки и CI/CD и современный технологический стек.
Стань частью сообщества разработчиков всей группы компаний (Yota, МегаФон, МегаЛабс, NetByNet) – создавай общие инструменты и обменивайся лучшими практиками.
Компания ищет:
Senior/Middle Java Developer - https://job.megafon.ru/vacancy/seniormiddle-java-developer-fabrika-mikroservisov
Quality Assurance engineer - https://job.megafon.ru/vacancy/quality-assurance-engineer-fabrika-mikroservisov
Python Developer - https://job.megafon.ru/vacancy/python-developer-fabrika-mikroservisov
Junior Java Developer - https://job.megafon.ru/vacancy/junior-java-developer-fabrika-mikroservisov
DevOps engineer - https://job.megafon.ru/vacancy/devops-engineer-fabrika-mikroservisov
Системный аналитик - https://job.megafon.ru/vacancy/sistemnyy-analitik-fabrika-mikroservisov
Фабрика базируется в Нижнем Новгороде и будет работать по гибким методологиям Agile, по принципу кросс-функциональных DevOps команд.
В распоряжении «фабрикантов» будут самые передовые инструменты разработки и CI/CD и современный технологический стек.
Стань частью сообщества разработчиков всей группы компаний (Yota, МегаФон, МегаЛабс, NetByNet) – создавай общие инструменты и обменивайся лучшими практиками.
Компания ищет:
Senior/Middle Java Developer - https://job.megafon.ru/vacancy/seniormiddle-java-developer-fabrika-mikroservisov
Quality Assurance engineer - https://job.megafon.ru/vacancy/quality-assurance-engineer-fabrika-mikroservisov
Python Developer - https://job.megafon.ru/vacancy/python-developer-fabrika-mikroservisov
Junior Java Developer - https://job.megafon.ru/vacancy/junior-java-developer-fabrika-mikroservisov
DevOps engineer - https://job.megafon.ru/vacancy/devops-engineer-fabrika-mikroservisov
Системный аналитик - https://job.megafon.ru/vacancy/sistemnyy-analitik-fabrika-mikroservisov
An Introduction to Super Resolution using Deep Learning
https://medium.com/beyondminds/an-introduction-to-super-resolution-using-deep-learning-f60aff9a499d
https://medium.com/beyondminds/an-introduction-to-super-resolution-using-deep-learning-f60aff9a499d
Medium
An Introduction to Super Resolution using Deep Learning
An elaborate discussion on the various Components, Loss Functions and Metrics used for Super Resolution using Deep Learning.
Plot of Randomly Generated Faces Using the Loaded GAN Model
How to Explore the GAN Latent Space When Generating Faces
https://machinelearningmastery.com/how-to-interpolate-and-perform-vector-arithmetic-with-faces-using-a-generative-adversarial-network/
How to Explore the GAN Latent Space When Generating Faces
https://machinelearningmastery.com/how-to-interpolate-and-perform-vector-arithmetic-with-faces-using-a-generative-adversarial-network/
Facebook is open-sourcing DLRM — a state-of-the-art deep learning recommendation model to help AI researchers and the systems and hardware community develop new, more efficient ways to work with categorical data.
fb: https://ai.facebook.com/blog/dlrm-an-advanced-open-source-deep-learning-recommendation-model/
link: https://arxiv.org/abs/1906.03109
fb: https://ai.facebook.com/blog/dlrm-an-advanced-open-source-deep-learning-recommendation-model/
link: https://arxiv.org/abs/1906.03109
Meta
We are open-sourcing a state-of-the-art deep learning recommendation model to help AI researchers and the systems and hardware…
Everything you need to know about TensorFlow 2.0
Keras-APIs, SavedModels, TensorBoard, Keras-Tuner and more.
https://hackernoon.com/everything-you-need-to-know-about-tensorflow-2-0-b0856960c074
Keras-APIs, SavedModels, TensorBoard, Keras-Tuner and more.
https://hackernoon.com/everything-you-need-to-know-about-tensorflow-2-0-b0856960c074
Hackernoon
Everything you need to know about TensorFlow 2.0 | HackerNoon
On June 26 of 2019, I will be giving a TensorFlow (TF) 2.0 workshop at the <a href="https://www.papis.io/latam-2019">PAPIs.io LATAM conference in São Paulo</a>. Aside from the happiness of being representing <a href="https://www.daitan.com/">Daitan</a> as…
PyTorchPipe
PyTorchPipe (PTP) is a component-oriented framework that facilitates development of computational multi-modal pipelines and comparison of diverse neural network-based models.
https://github.com/IBM/pytorchpipe
PyTorchPipe (PTP) is a component-oriented framework that facilitates development of computational multi-modal pipelines and comparison of diverse neural network-based models.
https://github.com/IBM/pytorchpipe
GitHub
GitHub - IBM/pytorchpipe: PyTorchPipe (PTP) is a component-oriented framework for rapid prototyping and training of computational…
PyTorchPipe (PTP) is a component-oriented framework for rapid prototyping and training of computational pipelines combining vision and language - GitHub - IBM/pytorchpipe: PyTorchPipe (PTP) is a co...
How to Develop a Conditional GAN (cGAN) From Scratch
Generative Adversarial Networks, or GANs, are an architecture for training generative models, such as deep convolutional neural networks for generating images.
Generative Adversarial Networks, or GANs, are an architecture for training generative models, such as deep convolutional neural networks for generating images.
Check the data science channel there you will find a lot of articles, links and advanced researches .
Join and learn hot topics of data science @opendatascience
Join and learn hot topics of data science @opendatascience
Literature of Deep Learning for Graphs
This is a paper list about deep learning for graphs.
https://github.com/DeepGraphLearning/LiteratureDL4Graph
This is a paper list about deep learning for graphs.
https://github.com/DeepGraphLearning/LiteratureDL4Graph
GitHub
GitHub - DeepGraphLearning/LiteratureDL4Graph: A comprehensive collection of recent papers on graph deep learning
A comprehensive collection of recent papers on graph deep learning - DeepGraphLearning/LiteratureDL4Graph
Forwarded from Artificial Intelligence
Rank-consistent Ordinal Regression for Neural Networks
Article: https://arxiv.org/abs/1901.07884
PyTorch: https://github.com/Raschka-research-group/coral-cnn
Article: https://arxiv.org/abs/1901.07884
PyTorch: https://github.com/Raschka-research-group/coral-cnn
arXiv.org
Rank consistent ordinal regression for neural networks with...
In many real-world prediction tasks, class labels include information about the relative ordering between labels, which is not captured by commonly-used loss functions such as multi-category...
How to Identify and Diagnose GAN Failure Modes
https://machinelearningmastery.com/practical-guide-to-gan-failure-modes/
https://machinelearningmastery.com/practical-guide-to-gan-failure-modes/
🤬1