​Top 10 Must Free Resource for Data Science and Machine Learning

🔗 Top 10 Must Free Resource for Data Science and Machine Learning
Must Read Books to kick start in AI | Machine Learning | Data Science Resource Links : Machine Learning Yearning By Andrew Ng http://www.mlyearning.org/ Thin...

​How to Create an Equally, Linearly, and Exponentially Weighted Average of Neural Network Model Weights in Keras
https://machinelearningmastery.com/polyak-neural-network-model-weight-ensemble/

🔗 How to Create an Equally, Linearly, and Exponentially Weighted Average of Neural Network Model Weigh
The training process of neural networks is a challenging optimization process that can often fail to converge. This can mean that the model at the end of training may not be a stable or best-performing set of weights to use as a final model. One approach to address this problem is to use an average …

​A Brief Introduction to Computational NeuroScience Part 1

🔗 A Brief Introduction to Computational NeuroScience Part 1
The Human Brain Intuition and Modelling

Deep Learning for NLP: PyTorch vs Tensorflow – Elvis Saravia – PyCon

🎥 Deep Learning for NLP: PyTorch vs Tensorflow – Elvis Saravia – PyCon Taiwan 2018
👁 1 раз ⏳ 3118 сек.
Day 2, R0 11:15–12:00

In this talk, I will discuss some of the best practices and latest trends in natural language processing (NLP) research. The main goal is to provide a comprehensive comparison between machine learning frameworks (PyTorch and Tensorflow) when used for NLP-related tasks, such as sentiment analysis and emotion recognition from textual data. I will cover how to program and train widely-used algorithms, such as neural word embeddings and long short-term memory (LSTM) networks, for sentence

​My First Adventures in NLP

https://towardsdatascience.com/my-first-adventures-in-nlp-631faa6aadd4?source=collection_home---4------0---------------------

🔗 My First Adventures in NLP – Towards Data Science
Exploring sentiment analysis as a “black box” and breaking it down to find insights.

​Remodelling machine learning: An AI that thinks like a scientist

🔗 Remodelling machine learning: An AI that thinks like a scientist
Modern machine learning is great for helping scientists sort through huge, unwieldy data sets. But it’s less useful for things that require inference or reas...

​Running Effective Machine Learning Teams: Common Issues, Challenges & Solutions | DataCouncil NYC'18

🔗 Running Effective Machine Learning Teams: Common Issues, Challenges & Solutions | DataCouncil NYC'18
ABOUT THE TALK: Despite significant progress in the deep learning space, implementing scalable machine learning pipelines still presents critical challenges....

​TensorFlow high-level APIs: Part 3 - Building and refining your models

🔗 TensorFlow high-level APIs: Part 3 - Building and refining your models
Welcome to Part 3 of our mini-series on TensorFlow high-level APIs! In this 3 part mini-series, TensorFlow Engineering Manager Karmel Allison runs us through...

🎥 lec23 Deep Learning
👁 1 раз ⏳ 4463 сек.

Kaggle YouTube-8M 2: классификация видео

🎥 Kaggle YouTube-8M 2: классификация видео — Глеб Стеркин, Владимир Алиев
👁 1 раз ⏳ 1272 сек.
Глеб Стеркин и Владимир Алиев вместе со своей командой заняли 4 место в конкурсе Kaggle The 2nd YouTube-8M Video Understanding Challenge. Как и в прошлом году стояла задача в классификации большого объёма видео, но в этот раз с ограничениями на размер модели. В видео участники рассказывают про использованные модели, многоуровневый подход с нейронными сетями и градиентным бустингом, сравнивают различные подходы.

Слайды: https://gh.mltrainings.ru/presentations/SterkinAliev_KaggleYT8M2_2018.pdf

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My First Adventures in NLP
https://towardsdatascience.com/my-first-adventures-in-nlp-631faa6aadd4?source=collection_home---4------3---------------------

​Machine Learning Cheatsheet.
Brief visual explanations of machine learning concepts with diagrams, code examples and links to resources for learning more.

🔗 Machine Learning Cheatsheet — ML Cheatsheet documentation

Kubernetes for Beginners

🎥 Kubernetes for Beginners
👁 1 раз ⏳ 665 сек.
Kubernetes is one of the highest velocity open source projects in history. Its a tool that enables developers to manage 'containerized' apps in the cloud easily. In this tutorial video, I'll deploy an image classifier app built in python to the cloud using Kubernetes. It's a 3 step process, and along the way I'll explain key concepts surrounding Docker, Google Cloud, and scalability. Enjoy!

Code for this video:
https://github.com/llSourcell/kubernetes

Please Subscribe! And Like. And comment. Thats what

🎥 Процесс решения задач глубокого машинного обучения
👁 3 раз ⏳ 683 сек.
Обобщенный процесс решения задачи глубокого машинного обучения:

1. Определение задачи и создание набора данных.
2. Выбор меры успеха.
3. Выбор протокола оценки.
4. Предварительная подготовка данных.
5. Разработка модели, более совершенной, чем базовый случай.
6. Масштабирование по вертикали: разработка модели с переобучением. Поиск границы между недообучением и переобучением.
7. Регуляризация модели и настройка гиперпараметров.

Источник: http://datascientist.one/sxema-resheniya-zadach-deep-learning/

​AWS re:Invent 2018: Machine Learning for the Enterprise, Sony Interactive Entertainment (ENT232-R1)

🔗 AWS re:Invent 2018: Machine Learning for the Enterprise, Sony Interactive Entertainment (ENT232-R1)
Machine learning is powering innovation across industries, including media & entertainment, healthcare, finance, and many more. In this session, representati...

​How Machine Learning can contribute to the day to day work

🔗 How Machine Learning can contribute to the day to day work
In this session you will: - Discover what Machine Learning really is through specific examples from real life - Understand other options to automate operatio...

​A Gentle Introduction to the Rectified Linear Activation Function for Deep Learning Neural Networks

🔗 A Gentle Introduction to the Rectified Linear Activation Function for Deep Learning Neural Networks
In a neural network, the activation function is responsible for transforming the summed weighted input from the node into the activation of the node or output for that input. The rectified linear activation function is a piecewise linear function that will output the input directly if is positive, otherwise, it will output zero. It has …

​Understanding Generative Adversarial Networks (GANs)

🔗 Understanding Generative Adversarial Networks (GANs)
Building, step by step, the reasoning that leads to GANs.

​Программист из Красноярска создал мобильное приложение на основе нейросетей и покоряет рынки России, США и Германии. NGS.RU расспросил предпринимателя об особенностях IT-бизнеса за рубежом, рынке труда в Соединённых Штатах и возможности монетизации идей. https://ngs24.ru/news/more/65698631/?from=window_2

🔗 Как программист из Красноярска сделал приложение для модников и открыл офис в США
Однажды программист из Красноярска Андрей Корхов съездил в Кремниевую долину в США и увлекся там изучением искусственного интеллекта.

​Free dataset for cardio rhythm classification
https://irhythm.github.io/cardiol_test_set/

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