​Deep learning cheatsheets, covering content of Stanford’s CS 230 class.

CNN: https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-convolutional-neural-networks
RNN: https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-recurrent-neural-networks
TipsAndTricks: https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-deep-learning-tips-and-tricks

#cheatsheet #Stanford #dl #cnn #rnn #tipsntricks

🔗 CS 230 - Convolutional Neural Networks Cheatsheet
Teaching page of Shervine Amidi, Graduate Student at Stanford University.

​Who is a Data Scientist? | How to become a Data Scientist? | Data Science Course | Edureka

🔗 Who is a Data Scientist? | How to become a Data Scientist? | Data Science Course | Edureka
** Data Scientist Masters' Program: https://www.edureka.co/masters-program/data-scientist-certification ** This Edureka video on "Who is a Data Scientist" wi...

How to Learn Data Science: Staying Motivated.
https://towardsdatascience.com/how-to-learn-data-science-staying-motivated-8665ed649687?source=collection_home---4------0---------------------

​How to Reduce Variance in the Final Deep Learning Model With a Horizontal Voting Ensemble

https://machinelearningmastery.com/horizontal-voting-ensemble/

🔗 How to Reduce Variance in the Final Deep Learning Model With a Horizontal Voting Ensemble
Predictive modeling problems where the training dataset is small relative to the number of unlabeled examples are challenging. Neural networks can perform well on these types of problems, although they can suffer from high variance in model performance as measured on a training or hold-out validation datasets. This makes choosing which model to use as …

​🔗 DL_17: Handling Color Image in Neural Network aka Stacked Auto Encoders (Denoising)
This lecture will discuss how to handle (feed) color images into stacked Auto Encoders.

​🔗 Stop Learning Frameworks
We are developers. We need to stay up to date with technology. Every day, we learn programming languages, frameworks, and libraries. The more modern tools we know — the better. Keeping up to date with Angular, React, Vue, Riot, Ember, Knockout is fun. But we are wasting our time.

​ОТКРЫТА ВАКАНСИЯ В ИНТЕРНЕТЕ !!ЗАРПЛАТА С ПЕРВОГО ДНЯ!! ЕЖЕДНЕВНАЯ ОПЛАТА от 3000р!!!!Основные обязанности рассылка рекламы!!!ОСТАЛОСЬ ВСЕГО 2 МЕСТА!!!! ВСЕ ВОПРОСЫ Екатерине

Олег Чумаков (Luden.io) - Машинное обучение для разработчиков игр 2018

🎥 Олег Чумаков (Luden.io) - Машинное обучение для разработчиков игр 2018
👁 1 раз ⏳ 1530 сек.
http://www.authorstream.com/Presentation/DevGAMM-3654731-machine-learning-game-developers-2018/

В рамках доклада будут освещены основные события мира машинного обучения за последние 2 года (со времени последнего доклада на эту тему на DevGAMM Москва 2017). Что происходит, как мы можем использовать это в разработке, что уже почти готово и появится буквально завтра.

NLP from machine learning to deep learning language models

🎥 Razvan Pistolea AIception – NLP from machine learning to deep learning language models
👁 1 раз ⏳ 6566 сек.
Razvan Pistolea, CTO at AIception

“You can’t handle the truth!”
https://towardsdatascience.com/you-cant-handle-the-truth-transfer-learning-to-detect-memorable-movie-quotes-d2b5305062cd?source=collection_home---4------5---------------------

https://habr.com/company/dataschool/blog/434540/

Что делать с людьми, которых заменят роботы?

#machinelearning #neuralnets #deeplearning #машинноеобучение

Наш телеграмм канал - https://yangx.top/ai_machinelearning_big_data

Machine Learning With Python | Machine Learning Tutorial

🎥 Machine Learning With Python | Machine Learning Tutorial | Python Machine Learning | Simplilearn
👁 1 раз ⏳ 3332 сек.
This Machine Learning with Python tutorial gives an introduction to Machine Learning and how to implement Machine Learning algorithms in Python. By the end of this video, you will be able to understand Machine Learning workflow, steps to download Anaconda, types of Machine Learning and hands-on in Python for Linear Regression and K-Means clustering algorithms. Below are the topics covered in this Machine Learning tutorial:

1. Why Machine Learning? ( 01:09 )
2. Applications of Machine Learning ( 01:50 )
3.

​Enabling Interactive Python & R on Hadoop – David Carlson

🔗 Enabling Interactive Python & R on Hadoop – David Carlson
Python and R are popular tools for data scientists to generate insights using data stored in Hadoop, but they can be difficult to use with larger teams in an...

​Garrett Smith - Introduction to AI engineering | Code Mesh LDN 18

🔗 Garrett Smith - Introduction to AI engineering | Code Mesh LDN 18
This video was recorded at Code Mesh LDN 18 http://bit.ly/2P7SPII Get involved in Code Sync's next conference http://bit.ly/2Mcm4aS --- INTRODUCTION TO AI EN...

Merry Christmas and Happy New Year
https://towardsdatascience.com/merry-christmas-and-happy-new-year-2843fe6ee83f?source=collection_home---2------1---------------------

​​​Overview of current state of autonomously driving vehicle by Ben Evans.

Not so technical overview of where first autonomous vehicles will become commodity.

Link: https://www.ben-evans.com/benedictevans/2018/3/26/steps-to-autonomy

🔗 Steps to autonomy
We talk a lot about levels of autonomy, and ask when the first ‘fully autonomous’ cars will appear. That might be the wrong way to look at it - there will be lots of different kinds of ‘autonomy’, and the ‘where’ and ‘what’ may matter as much as the ‘when’.

TMPA School 2018 Saratov: Кластеризация дефектов в программном обеспечении

https://www.youtube.com/watch?v=AwL-WEeCRyY

🎥 TMPA School 2018 Saratov: Кластеризация дефектов в программном обеспечении (часть 1)
👁 2 раз ⏳ 3068 сек.
Анна Громова, кандидат технических наук, руководитель отдела анализа данных, Exactpro

Смотреть презентацию: https://speakerdeck.com/exactpro/klastierizatsiia-diefiektov-v-proghrammnom-obiespiechienii-bab4cebb-5f13-45ba-8e9c-365839545852

Продолжение: https://youtu.be/1_rjXXC9r5w
Дополнительные материалы: https://youtu.be/wNKgayqEt84

TMPA School 2018
Тестирование программного обеспечения, анализ данных и машинное обучение
https://school.tmpaconf.org/

35C3 - Introduction to Deep Learning

🎥 35C3 - Introduction to Deep Learning
👁 1 раз ⏳ 2467 сек.
https://media.ccc.de/v/35c3-9386-introduction_to_deep_learning



This talk will teach you the fundamentals of machine learning and give you a sneak peek into the internals of the mystical black box. You'll see how crazy powerful neural networks can be and understand why they sometimes fail horribly.

Computers that are able to learn on their own. It might have sounded like science-fiction just a decade ago, but we're getting closer and closer with recent advancements in Deep Learning. Or are we?

In this t