ДЛ
В которой, в теории, можно заставить работать аналитиков, а не разработчиков
Size: a a a
2020 November 11
ДЛ
Это выводы из "поигрался". Как оно в реальной жизни - не скажу
NN
ну да, было бы интересно про продакшен использование послушать)
2020 November 14
e
2020 November 15
r
кто-нибудь пользовался им?
В продакшене юзаем диноду.
r
Однако у нас не оч много юзкейсов с ней. В основном это забрать данные с реста и отдать данные рестом. На диноде это оч просто сделать.
r
Но, с другой стороны, если у тебя разнородные источники, то сделать общий view по ним, причём просто - это прям очень круто
Да, это в принципе основное, для чего виртуализация надо.
CO
Всем привет, а есть ли люди которые работает в фарм компаниях, есть точечный вопрос про введение строгой документации для регистрации продуктов
LV
По denodo. Мы будем доклад по ним делать. Если пустим в публичную сферу, скину сюда.
LV
И если есть какие-то вопросы по ней, пишите сюда или в личку. Попробую достать ответы.
2020 November 16
2020 November 17
I
Что именно интересует? Можем в пм пообщаться
2020 November 18
e
Danny Ma:.
-----
I'm a #DataScientist and I am SICK of buzzwords and popular catch phrases so I decided to translate them in simple terms.
Artificial Intelligence = linear regression & decision trees
Smart Algorithms = random forest
Next-Gen machine learning = boosted trees
AutoML = import autosklearn
Intelligent Automation = Windows scheduler, crontab
MLOps = docker
Analytics at scale = no more excel
Customer-centric data lake = we have customer_id in our database tables
Serverless Architecture = I have no idea what a server is
Cloud APIs = my dev-ops guy made me click some link
Advanced Analytics = SQL
DataViz Guru = library(ggplot2)
Data Consultant = often draws convenient conclusions from data
Advanced ML/DL = Python
Image Recognition = MNIST
NLP Experts = transfer learning on GTP-3/Bert
Reproducible experiments = jupyter notebooks
Maintain source code = git add . && git commit -m "yolo" && git push origin master
Distributed Analytics = no more MySQL on a laptop
Experimentation Framework = z-tests
Advanced Statistics = random control groups
Customer loyalty focus = we spam them with emails
Centre of Excellence = fancy team name to justify payrises
HR analytics = people leave, we didn't pay them enough
Do you agree? Did I miss anything?
-----
I'm a #DataScientist and I am SICK of buzzwords and popular catch phrases so I decided to translate them in simple terms.
Artificial Intelligence = linear regression & decision trees
Smart Algorithms = random forest
Next-Gen machine learning = boosted trees
AutoML = import autosklearn
Intelligent Automation = Windows scheduler, crontab
MLOps = docker
Analytics at scale = no more excel
Customer-centric data lake = we have customer_id in our database tables
Serverless Architecture = I have no idea what a server is
Cloud APIs = my dev-ops guy made me click some link
Advanced Analytics = SQL
DataViz Guru = library(ggplot2)
Data Consultant = often draws convenient conclusions from data
Advanced ML/DL = Python
Image Recognition = MNIST
NLP Experts = transfer learning on GTP-3/Bert
Reproducible experiments = jupyter notebooks
Maintain source code = git add . && git commit -m "yolo" && git push origin master
Distributed Analytics = no more MySQL on a laptop
Experimentation Framework = z-tests
Advanced Statistics = random control groups
Customer loyalty focus = we spam them with emails
Centre of Excellence = fancy team name to justify payrises
HR analytics = people leave, we didn't pay them enough
Do you agree? Did I miss anything?
MV
Danny Ma:.
-----
I'm a #DataScientist and I am SICK of buzzwords and popular catch phrases so I decided to translate them in simple terms.
Artificial Intelligence = linear regression & decision trees
Smart Algorithms = random forest
Next-Gen machine learning = boosted trees
AutoML = import autosklearn
Intelligent Automation = Windows scheduler, crontab
MLOps = docker
Analytics at scale = no more excel
Customer-centric data lake = we have customer_id in our database tables
Serverless Architecture = I have no idea what a server is
Cloud APIs = my dev-ops guy made me click some link
Advanced Analytics = SQL
DataViz Guru = library(ggplot2)
Data Consultant = often draws convenient conclusions from data
Advanced ML/DL = Python
Image Recognition = MNIST
NLP Experts = transfer learning on GTP-3/Bert
Reproducible experiments = jupyter notebooks
Maintain source code = git add . && git commit -m "yolo" && git push origin master
Distributed Analytics = no more MySQL on a laptop
Experimentation Framework = z-tests
Advanced Statistics = random control groups
Customer loyalty focus = we spam them with emails
Centre of Excellence = fancy team name to justify payrises
HR analytics = people leave, we didn't pay them enough
Do you agree? Did I miss anything?
-----
I'm a #DataScientist and I am SICK of buzzwords and popular catch phrases so I decided to translate them in simple terms.
Artificial Intelligence = linear regression & decision trees
Smart Algorithms = random forest
Next-Gen machine learning = boosted trees
AutoML = import autosklearn
Intelligent Automation = Windows scheduler, crontab
MLOps = docker
Analytics at scale = no more excel
Customer-centric data lake = we have customer_id in our database tables
Serverless Architecture = I have no idea what a server is
Cloud APIs = my dev-ops guy made me click some link
Advanced Analytics = SQL
DataViz Guru = library(ggplot2)
Data Consultant = often draws convenient conclusions from data
Advanced ML/DL = Python
Image Recognition = MNIST
NLP Experts = transfer learning on GTP-3/Bert
Reproducible experiments = jupyter notebooks
Maintain source code = git add . && git commit -m "yolo" && git push origin master
Distributed Analytics = no more MySQL on a laptop
Experimentation Framework = z-tests
Advanced Statistics = random control groups
Customer loyalty focus = we spam them with emails
Centre of Excellence = fancy team name to justify payrises
HR analytics = people leave, we didn't pay them enough
Do you agree? Did I miss anything?
🤣 прикольно
Н
Danny Ma:.
-----
I'm a #DataScientist and I am SICK of buzzwords and popular catch phrases so I decided to translate them in simple terms.
Artificial Intelligence = linear regression & decision trees
Smart Algorithms = random forest
Next-Gen machine learning = boosted trees
AutoML = import autosklearn
Intelligent Automation = Windows scheduler, crontab
MLOps = docker
Analytics at scale = no more excel
Customer-centric data lake = we have customer_id in our database tables
Serverless Architecture = I have no idea what a server is
Cloud APIs = my dev-ops guy made me click some link
Advanced Analytics = SQL
DataViz Guru = library(ggplot2)
Data Consultant = often draws convenient conclusions from data
Advanced ML/DL = Python
Image Recognition = MNIST
NLP Experts = transfer learning on GTP-3/Bert
Reproducible experiments = jupyter notebooks
Maintain source code = git add . && git commit -m "yolo" && git push origin master
Distributed Analytics = no more MySQL on a laptop
Experimentation Framework = z-tests
Advanced Statistics = random control groups
Customer loyalty focus = we spam them with emails
Centre of Excellence = fancy team name to justify payrises
HR analytics = people leave, we didn't pay them enough
Do you agree? Did I miss anything?
-----
I'm a #DataScientist and I am SICK of buzzwords and popular catch phrases so I decided to translate them in simple terms.
Artificial Intelligence = linear regression & decision trees
Smart Algorithms = random forest
Next-Gen machine learning = boosted trees
AutoML = import autosklearn
Intelligent Automation = Windows scheduler, crontab
MLOps = docker
Analytics at scale = no more excel
Customer-centric data lake = we have customer_id in our database tables
Serverless Architecture = I have no idea what a server is
Cloud APIs = my dev-ops guy made me click some link
Advanced Analytics = SQL
DataViz Guru = library(ggplot2)
Data Consultant = often draws convenient conclusions from data
Advanced ML/DL = Python
Image Recognition = MNIST
NLP Experts = transfer learning on GTP-3/Bert
Reproducible experiments = jupyter notebooks
Maintain source code = git add . && git commit -m "yolo" && git push origin master
Distributed Analytics = no more MySQL on a laptop
Experimentation Framework = z-tests
Advanced Statistics = random control groups
Customer loyalty focus = we spam them with emails
Centre of Excellence = fancy team name to justify payrises
HR analytics = people leave, we didn't pay them enough
Do you agree? Did I miss anything?
Омг, он всех сдал :)
MV
Тут ещё не хватает
Data Lake - xls in hdfs instead of email 😅
Data Lake - xls in hdfs instead of email 😅
VK
Тут ещё не хватает
Data Lake - xls in hdfs instead of email 😅
Data Lake - xls in hdfs instead of email 😅
👍
Н
Тут ещё не хватает
Data Lake - xls in hdfs instead of email 😅
Data Lake - xls in hdfs instead of email 😅
2020 November 19
e
Может кто порекомендует курсы по spark ? Или толковую книжку ?
NN
Может кто порекомендует курсы по spark ? Или толковую книжку ?
Пока лучше definitive guide, кажется, ничего не написали. Курсы в основном, на мой взгляд, УГ, но это если ищете что-то продвинутое. Для начального уровня почти любые подойдут. Правда, в основном они на питоне, на скале реже встречаются.