Personal Information
Unternehmen/Arbeitsplatz
Stockholm, Sweden Sweden
Beruf
Machine Learning Engineer / Data Scientist
Branche
Finance / Banking / Insurance
Webseite
http://eyad.ninja
Info
Artificial Intelligence, Data Mining, Scientific Applications, Databases, Data Analysis, Statistical Analysis Pythonista, Big Data, Data Science, Machine Learning, Deep Learning
- Präsentationen
- Dokumente
- Infografiken
What's Next: Social Media Trends 2020
Ogilvy Consulting
•
Vor 4 Jahren
Scala Data Pipelines for Music Recommendations
Chris Johnson
•
Vor 9 Jahren
10 more lessons learned from building Machine Learning systems
Xavier Amatriain
•
Vor 8 Jahren
Everyday I'm Shuffling - Tips for Writing Better Spark Programs, Strata San Jose 2015
Databricks
•
Vor 9 Jahren
Intro To MongoDB
Alex Sharp
•
Vor 14 Jahren
Kaggle Winning Solution Xgboost algorithm -- Let us learn from its author
Vivian S. Zhang
•
Vor 8 Jahren
word2vec, LDA, and introducing a new hybrid algorithm: lda2vec
👋 Christopher Moody
•
Vor 8 Jahren
Feature Engineering
HJ van Veen
•
Vor 7 Jahren
Building a real time, solr-powered recommendation engine
Trey Grainger
•
Vor 11 Jahren
Tips for data science competitions
Owen Zhang
•
Vor 8 Jahren
10 Lessons Learned from Building Machine Learning Systems
Xavier Amatriain
•
Vor 9 Jahren
Open Source Tools & Data Science Competitions
odsc
•
Vor 8 Jahren
General Tips for participating Kaggle Competitions
Mark Peng
•
Vor 8 Jahren
Statistical Machine Learning for Text Classification with scikit-learn and NLTK
Olivier Grisel
•
Vor 13 Jahren
Understanding Random Forests: From Theory to Practice
Gilles Louppe
•
Vor 9 Jahren
Lesson 35: Game Theory and Linear Programming
Matthew Leingang
•
Vor 16 Jahren
How to become a data scientist in 6 months
Tetiana Ivanova
•
Vor 8 Jahren
Kaggle Otto Challenge: How we achieved 85th out of 3,514 and what we learnt
Eugene Yan Ziyou
•
Vor 8 Jahren
Deep Learning for Recommender Systems
Yves Raimond
•
Vor 6 Jahren
Tips and tricks to win kaggle data science competitions
Darius Barušauskas
•
Vor 7 Jahren