​Speed Up Your Exploratory Data Analysis With Pandas-Profiling

🔗 Speed Up Your Exploratory Data Analysis With Pandas-Profiling
Get an intuition of your data’s structure with just one line of code

​Raising a child vs Training a machine

🔗 Raising a child vs Training a machine
The mom’s point of view on Machine Learning

🎥 L24/4 Seq2sen with Attention in Python
👁 1 раз ⏳ 638 сек.
Dive into Deep Learning
UC Berkeley, STAT 157

Slides are at
http://courses.d2l.ai
The book is at
http://www.d2l.ai

Naive Bayes Classifiers

​Data Minds: Evan Chow — Data Scientist at Snapchat

🔗 Data Minds: Evan Chow — Data Scientist at Snapchat
Data Minds is a series that profiles professionals working with data. In this series, you’ll learn about their story, day-to-day, and…

🎥 Deep Learning Weekly-1. Neural Ordinary Differential Equations
👁 1 раз ⏳ 4251 сек.
Первый доклад в рамках еженедельного семинара DeepLearning Weekly

Код с примером (Julia): https://yadi.sk/d/BKD-Etsjf3fwUQ

🎥 Машинное обучение 11. Свёрточные нейросети
👁 1 раз ⏳ 4808 сек.
Лекция от 23.04.2019
Лектор: Радослав Нейчев

Снимал: Михаил Кревский
Монтировал: Алексей Козинов

​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