interpretableml.ai

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Home - SERG.ai

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Home - SERG.ai

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The aspiration is to provide the often-missing link between data and decision-making, by identifying patterns & relationships, and formulating predictions.

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Egendom Innehåll
locale en_US
type website
title Home - SERG.ai
description The aspiration is to provide the often-missing link between data and decision-making, by identifying patterns & relationships, and formulating predictions.
url https://www.serg.ai/
site_name SERG.ai
image https://www.serg.ai/wp-content/uploads/2019/11/drowsiness_1.png
image:width 592
image:height 560
image:type image/png

Rubriker

H1 H2 H3 H4 H5 H6
1 9 20 163 19 0
  • [H1] Serg Masís
  • [H2] Serg Masís
  • [H2] Resume
  • [H2] Writing
  • [H2] ⭐⭐⭐⭐⭐
  • [H2] 🔥 pre-order now🔥
  • [H2] Speaking
  • [H2] Blog
  • [H2] Portfolio
  • [H2] Contact
  • [H3] What I Do
  • [H3] Affiliations
  • [H3] Experience
  • [H3] Education
  • [H3] Personal
  • [H3] Data Wrangling & Statistical Analysis
  • [H3] Machine Learning
  • [H3] Computer Vision
  • [H3] Data Visualization
  • [H3] Big Data & Distributed Systems
  • [H3] Web & Mobile Development
  • [H3] Computer Graphics
  • [H3] Project Management
  • [H3] Operating Systems & Server Config
  • [H3] Interpretable Machine Learning with Python—Oct. 2023
  • [H3] DIY AI: Step-By-Step Artificial Intelligence Projects for Makers and Hackers—May. 2026!
  • [H3] Building Responsible AI with Python: Learn to identify and mitigate bias with hands-on code examples—Dec. 2026!
  • [H3] Upcoming
  • [H3] Past Events
  • [H3] How Can I Help You?
  • [H4] Analytics & Visualization
  • [H4] Deployment & Evaluation
  • [H4] Predictive Modelling & Interpretation
  • [H4] Management, Writing & Speaking
  • [H4] Author
  • [H4] Climate & Agronomic Data Scientist
  • [H4] Data Scientist | Systems Analyst Fellow
  • [H4] Head of Product Development | Co-Founder
  • [H4] Webmaster
  • [H4] Mobile App Developer | Client-Side Architect
  • [H4] Product & Brand Developer | Founder
  • [H4] Project Manager | Online Marketing Consultant
  • [H4] Director of Web Development
  • [H4] C# Software Developer
  • [H4] 3D Modeling, Intern
  • [H4] Web Developer | Project Manager
  • [H4] Master’s in Data Science
  • [H4] BS in Computer Science Engineering
  • [H4] Languages
  • [H4] Additional Skills
  • [H4] Hobbies
  • [H4] Python (Pandas, Numpy, SciPy, StatsModel, NLTK, Gensim,...)
  • [H4] R (Tidyverse, Caret, purrr...)
  • [H4] SQL (most variations)
  • [H4] Excel (Pivot tables, vlookup, VBA)
  • [H4] Tableau Prep
  • [H4] TF/Keras
  • [H4] Scikit-learn
  • [H4] Interpretability (SHAP, LIME,...)
  • [H4] R (randomForest, lme4, glmnet,...)
  • [H4] PyTorch
  • [H4] XGBoost, Catboost, LightGBM
  • [H4] Tuning & Experimentation (Hyperopt, Weights & Biases..)
  • [H4] Distributed Training (Elephas, Horovod)
  • [H4] OpenCV
  • [H4] DLib
  • [H4] PIL
  • [H4] Python (Matplotlib, Seaborn)
  • [H4] R (Ggplot, Plotly, Leaflet)
  • [H4] Tableau Desktop
  • [H4] D3.js
  • [H4] MongoDB
  • [H4] Elasticsearch
  • [H4] Apache Spark
  • [H4] MapReduce
  • [H4] Neo4j
  • [H4] Hive
  • [H4] Pig
  • [H4] PHP
  • [H4] Flask
  • [H4] NodeJS
  • [H4] .NET
  • [H4] HTML + CSS + Javascript
  • [H4] jQuery
  • [H4] nginx
  • [H4] Java
  • [H4] Objective C
  • [H4] Swift
  • [H4] Adobe Photoshop
  • [H4] Adobe Illustrator
  • [H4] Adobe After Effects
  • [H4] Autodesk 3d Studio Max
  • [H4] Rhino 3D
  • [H4] Agile Methodologies
  • [H4] Team Leadership
  • [H4] Public Speaking
  • [H4] Git (also Github/Bitbucket)
  • [H4] Trello
  • [H4] Asana
  • [H4] MacOS (inc. Terminal)
  • [H4] Ubuntu / CentOS (inc. Command Line)
  • [H4] Windows
  • [H4] Shell Scripts (and Crontab)
  • [H4] Python Virtualenv
  • [H4] Docker
  • [H4] Build Stuff 2022 (Vilnius, Lithuania) 🇱🇹
  • [H4] Compass AI & Data Summit (Budapest, Hungary) 🇭🇺
  • [H4] AI Summer of Code 🇳🇬
  • [H4] Packt Machine Learning Summit 2025 🇬🇧
  • [H4] ODSC East 2025 10-year Anniversary (Boston, MA) 🇺🇸
  • [H4] Raleigh AI, Machine Learning, and Computer Vision Meetup (Chapel Hill, NC) 🇺🇸
  • [H4] AV DataHour 🇮🇳
  • [H4] DATAcated Events 🇺🇸
  • [H4] Data Day Texas (Austin, TX) 🇺🇸
  • [H4] Global AI Conference 2024 🇺🇸
  • [H4] Øredev 2024 (Malmö) 🇸🇪
  • [H4] ODSC West 2024 (San Francisco, CA) 🇺🇸
  • [H4] Data Makers Fest 2024 (Porto) 🇵🇹
  • [H4] Nebraska.Code() 2024 (Lincoln, NE) 🇺🇸
  • [H4] ON HIATUS
  • [H4] ODSC West 2023 (San Francisco, CA) 🇺🇸
  • [H4] MLOps World + Generative AI World Summit 2023 (Austin, TX) 🇺🇸
  • [H4] ML Conference Munich 2023 🇩🇪
  • [H4] Infoshare 2023 (Gdańsk) 🇵🇱
  • [H4] Data Innovation Summit 2023 (Stockholm) 🇸🇪
  • [H4] KMD Steam 2023 (Copenhagen) 🇩🇰
  • [H4] DeveloperWeek Europe 2023 🇪🇺
  • [H4] Semantic Layer Summit 2023 🇺🇸
  • [H4] Convergence 2023 🇺🇸
  • [H4] ML Berlin Hybrid Conference 2022 🇩🇪
  • [H4] Build Stuff 2022 (Vilnius, Lithuania) 🇱🇹
  • [H4] ODSC West 2022 (San Francisco, CA) 🇺🇸
  • [H4] Code PaLOUsa 2022 (Louisville, KY) 🇺🇸
  • [H4] ML Summit Munich 2022 🇩🇪
  • [H4] Geekle Data Science Global Summit 2022 🇺🇸🇪🇺
  • [H4] WeAreDevelopers World Congress 2022 🇩🇪
  • [H4] DTC Online Event 🇩🇪
  • [H4] Data Science Salon Virtual 🇺🇸
  • [H4] ODSC East 2022 (Boston, MA) 🇺🇸
  • [H4] WinHacks 2022 🇨🇦
  • [H4] AI Dev Conference @ DeveloperWeek 🇺🇸
  • [H4] SuperDataScience Podcast #539 🇺🇸
  • [H4] Live Sessions by Experts 🇧🇪
  • [H4] AI X Summit 2021 🇺🇸
  • [H4] Great North DevFest 2021 🇨🇦
  • [H4] WUR AI Workshop 2021 🇳🇱
  • [H4] Ai4 2021 Enterprise 🇺🇸
  • [H4] AIExpo 2021 🇺🇸
  • [H4] Global AI Conference 2021 🇺🇸
  • [H4] Strangeloop 2021 (St. Louis, MO) 🇺🇸
  • [H4] A.I. Startups San Francisco Meetup 🇺🇸
  • [H4] A.I. Access Series 🇯🇵🇺🇸
  • [H4] ML Summit Berlin 2021 🇩🇪
  • [H4] DataScienceGO Virtual April 2021 🇺🇸
  • [H4] Python for ML and AI Global Summit 2021 🇺🇸🇪🇺
  • [H4] Aggregate Intellect ML Interpretability Stream 🇨🇦
  • [H4] Machine Learning Prague 2021 🇨🇿
  • [H4] DSGO Connect February 2021 🇺🇸
  • [H4] PyData Chicago 🇺🇸
  • [H4] Open Data Science Conference West 2020 🇺🇸
  • [H4] Strangeloop 2019 (St. Louis, MO) 🇺🇸
  • [H4] 8th Light University 🇺🇸
  • [H4] The One-model-fits-all fallacy
  • [H4] How to “make it” in any field?
  • [H4] The Downward Spiral of Bias in Machine Learning
  • [H4] You are not alone!
  • [H4] With Great Power Comes Great Responsibility
  • [H4] Navigating the World of Data Science
  • [H4] Happy π Day!
  • [H4] Analog computing makes a comeback
  • [H4] Rate my setup…
  • [H4] Pathways to the Future of AI
  • [H4] Book Review: Causal Inference — The Mixtape
  • [H4] What frightens me the most
  • [H4] Fairness is often about consistent rules
  • [H4] Trust is mission-critical
  • [H4] Why does Interpretable Machine Learning matter?
  • [H4] Not All is Lost from My Biggest Failure
  • [H4] Opinion: Resource Constraints Foster Creative Solutions
  • [H4] Opinion: What Makes Us Care?
  • [H4] Smart Grid Short Term Load Forecasting with RNNs
  • [H4] Audio-Assisted Lip-Reading System Using LSTM Artificial Neural Network
  • [H4] Haiku Generation with the GPT-2 language model
  • [H4] Predicting 3D Printer Failure
  • [H4] 3D Scanning Via Photogrammetry with Automated Stage
  • [H4] Data Quality Assessment on a Data Warehouse and KPI Assessment on Its Users
  • [H4] Interpretable Personal Loan Default Predictions
  • [H4] Chicago Hospital Ranking System
  • [H4] Predicting Rugby 7s Positions with Match-Play Statistics
  • [H4] Estimating Driver Drowsiness & Distraction with Deep Learning & Computer Vision
  • [H4] A Regression-based Cross-Sectional Analysis of the Effects of Resources on Math Proficiency
  • [H4] Search Engine for Spontaneous and Serendipitous Decision Making
  • [H4] Online Poker Analytics
  • [H5] 20 years experience
  • [H5] 2020-
  • [H5] 2020-
  • [H5] 2019
  • [H5] 2015 - 2017
  • [H5] 2013 - 2016
  • [H5] 2011 - 2013
  • [H5] 2010-2013
  • [H5] 2009-2011
  • [H5] 2004-2009
  • [H5] 2002-2004
  • [H5] 2002, Winter
  • [H5] 2001-2003
  • [H5] 2019
  • [H5] 2009
  • [H5] 3 Exciting Books!
  • [H5] My ramblings, rants & raves
  • [H5] My Projects
  • [H5] Get in Touch

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odsc summit models data talk machine video interpretable learning workshop

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Nyckelord Innehåll Titel Nyckelord Beskrivning Rubriker
learning 41
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talk 32
video 20
data 18

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