​This Google Experiment Destroyed Some of the Assumptions of Representation Learning

🔗 This Google Experiment Destroyed Some of the Assumptions of Representation Learning
Building knowledge in high dimensional datasets is one of the fundamental challenges of modern deep learning applications. As humans, we…

🎥 The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
👁 1 раз ⏳ 4416 сек.
This talk, titled The 7 Reasons Most Machine Learning Funds Fail, looks at the particularly high rate of failure in financial machine learning. The few managers who succeed amass a large number of assets, deliver consistently exceptional performance to their investors. However, that is a rare outcome. This presentation will go over the 7 critical mistakes underlying most financial machine learning failures based off of Marcos López de Prado’s experiences and observations.

To learn more about Quantopian, vi

🎥 Transforming Healthcare With Machine Learning (Cloud Next '19)
👁 1 раз ⏳ 2558 сек.
With the wealth of medical imaging and text data available, there’s a big opportunity for machine learning to optimize healthcare workflows. In this talk, we’ll provide an overview of the Cloud ML products that can help with healthcare scenarios, including AutoML Vision, Cloud Natural Language, and BigQuery ML. Then we’ll hear from IDEXX, a veterinary diagnostics company using AutoML Vision to classify radiology images.


Beyond Just Speech-To-Text → https://bit.ly/2TS6twZ

Watch more:
Next '19 ML & AI Ses

​Microsoft представил набор из 14 программных функций для VR-устройств, упрощающих восприятие виртуального мира для слабовидящих людей.

Решения помогут пользователям своевременно обнаруживать препятствия и лучше ориентироваться в пространстве: http://amp.gs/UzEB

🔗 Microsoft адаптировала виртуальную реальность для слабовидящих людей
Специалисты Microsoft создали набор из 14 инструментов, позволяющих людям с нарушениями зрения лучше воспринимать виртуальную реальность. Компания Microsoft пр...

🎥 40 - Машинное обучение. Метод опорных векторов (support vector machine, SVM)
👁 1 раз ⏳ 240 сек.
Лектор: Артём Шевляков

https://stepik.org/8057

​ПО для управления роборукой, автоматически определяющее её конфигурацию

🔗 ПО для управления роборукой, автоматически определяющее её конфигурацию
Если вы когда-нибудь писали ПО для управления роборукой или вообще любым роботоподобным механизмом с числом степеней свободы более трёх, то знаете, что большую...

🎥 Kaggle Live-Coding: Code Reviews! Class imbalanced in Python | Kaggle
👁 1 раз ⏳ 4049 сек.
Today we'll be reviewing code instead of writing our own. We'll be looking for:

🐞 bugs the authors might have missed
🎿 places we can improve efficiency
🔡 confusing names/comments

Link to code:
- "Dealing with unbalance: EDA,PCA,SMOTE,LR,SVM,DT,RF" by Alexander Abstreiter, https://www.kaggle.com/ambpro/dealing-with-unbalance-eda-pca-smote-lr-svm-dt-rf

SUBSCRIBE : http://www.youtube.com/user/kaggledot...

About Kaggle:
Kaggle is the world's largest community of data scientists. Join us to compete, collab

​Top 10 Coding Mistakes Made by Data Scientists

🔗 Top 10 Coding Mistakes Made by Data Scientists
A data scientist is “ … better at software engineering than any statistician”. Learn common coding mistakes to avoid

​Наш телеграм канал - tglink.me/ai_machinelearning_big_data

🔗 Analyzing Employee Reviews: Google vs Amazon vs Apple vs Microsoft
Which company is it worth working for?

​Zilic: Detect any disease with machine learning

🔗 Zilic: Detect any disease with machine learning
Using machine learning to detect any disease with a single test

🎥 Women in Data Science: Elaine Nsoesie, Applications of Machine Learning to Global Health Problems
👁 1 раз ⏳ 1457 сек.
Women in Data Science Boston Conference 2019
Elaine Nsoesie
Applications of Machine Learning to Global Health Problems

​Приглашаем выступить на PyCon Russia 2019

🔗 Приглашаем выступить на PyCon Russia 2019
Всем привет! Седьмой PyConRu пройдёт 24-25 июня в отеле «Cronwell Яхонты Таруса» в 95 км от Москвы. У PyConRu особенный формат: два дня участники и докладчики...

​How I Passed the Google Cloud Professional Data Engineer Certification Exam

🔗 How I Passed the Google Cloud Professional Data Engineer Certification Exam
Without the recommended 3-years hands-on experience

​Open Minded AI: Improving Performance by Keeping All Options on the Table

🔗 Open Minded AI: Improving Performance by Keeping All Options on the Table
How I made my Reinforcement Learning agent perform better by making it stop going naively after the highest reward

​Вдохновлялись продакшеном и баскетболом: как Яндекс готовит чемпионат по программированию

🔗 Вдохновлялись продакшеном и баскетболом: как Яндекс готовит чемпионат по программированию
В конце мая начнётся наш чемпионат по программированию. Он будет проходить в онлайне и позволит проверить себя в одной из четырёх сфер: бэкенд- или фронтенд-разр...

​Counting Pizza: Metrics for Machine Learning

🔗 Counting Pizza: Metrics for Machine Learning
Visually understanding machine learning metrics

​Plot of Convolutional Neural Network Architecture With a Efficient Inception Module
How to Implement VGG, Inception and ResNet Modules for Convolutional Neural Networks from Scratch

https://machinelearningmastery.com/how-to-implement-major-architecture-innovations-for-convolutional-neural-networks/

🔗 How to Implement VGG, Inception and ResNet Modules for Convolutional Neural Networks from Scratch
There are discrete architectural elements from milestone models that you can use in the design of your own convolutional neural networks. Specifically, models that have achieved state-of-the-art results for tasks like image classification use discrete architecture elements repeated multiple times, such as the VGG block in the VGG models, the inception module in the GoogLeNet, …

​TensorFlow Lite Now Faster with Mobile GPUs (Developer Preview)

🔗 TensorFlow Lite Now Faster with Mobile GPUs (Developer Preview)
Posted by the TensorFlow team

🎥 Building a high-resolution computational atlas of the whole human brain
👁 1 раз ⏳ 2957 сек.
Building a high-resolution computational atlas of the whole human brain with histology, deep learning, and Bayesian modeling: FreeSurfer implementation and application to population studies.

Juan Eugenio Iglesias
ERC Senior Research Fellow
University College London
Research staff, Martinos Center
Research Affiliate, MIT
BrainMap Seminar Series, 11/28/2018

Athinoula A. Martinos Center for Biomedical Imaging
https://www.martinos.org/
Follow @MGHMartinos on Facebook, Instagram + Twitter!

🎥 Paper Review Calls 011 -- U-Net: Convolutional Networks for Biomedical Image Segmentation
👁 1 раз ⏳ 5255 сек.
U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger et al, 15

Roll up everybody! Join Karol Zak for a review of this seminal paper on semantic segmentation. Semantic segmentation is a popular task in computer vision to assign each pixel in an image to a class in a supervised fashion. Karol is our top expert in semantic segmentation (in CSE) and has been involved in several fascinating projects using it!

https://arxiv.org/pdf/1505.04597.pdf

"Abstract. There is large consent that