interpretableml.ai

Revisión web de interpretableml.ai

Home - SERG.ai

 Generado el 05 Febrero 2026 18:58 PM

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Título

Home - SERG.ai

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Descripción

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

Longitud : 155

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Propiedad Contenido
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

Titulos

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

Imagenes

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Enlaces en página

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Serg Masís Externo Pasando Jugo
Interpretable Machine Learning with Python Interna Pasando Jugo
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"Prompt Darwinism: Evolutionary Engineering in the Age of LLMs" Externo Pasando Jugo
"Hands-on Agentic AI with GraphRAG and MCP tools use" Externo Pasando Jugo
"AISOC Workshop: Scaling Machine Learning Reliability with Interpretability" Externo Pasando Jugo
"Interpretability by Design: Exploring Rule-Based Models in Machine Learning" Externo Pasando Jugo
"Harvesting Trust: How to Make Trustworthy Specialist Conversational AI Agents" Externo Pasando Jugo
"Agentic AI Design Patterns" Externo Pasando Jugo
"Mastering Agentic AI Design Patterns for Scalable Systems" Externo Pasando Jugo
"Let's talk about the AI AGENTS in the room" Externo Pasando Jugo
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"Harvesting Trust: A Case Study on Developing Dependable Specialist Chatbots" Externo Pasando Jugo
"Harvesting Trust: Methods for Validating Chatbots in Agriculture" Externo Pasando Jugo
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"Beyond Code: The Essential AI Skillsets for Development Teams" Externo Pasando Jugo
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"QA for ML: How we can trust AI with food sustainability" Externo Pasando Jugo
"QA for ML: How we can trust AI with food sustainability" Externo Pasando Jugo
"Beyond Code: The Essential AI Skillsets for Development Teams" Externo Pasando Jugo
"Facial Recognition from Scratch with Python and JS" Externo Pasando Jugo
"Quality Assurance (QA) in Machine Learning" Externo Pasando Jugo
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"Interpreting NLP Transformers" Externo Pasando Jugo
"Introduction to Explainable AI" Externo Pasando Jugo
"DIY AI: Facial Recognition from Scratch" Externo Pasando Jugo
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"Come play with AI! The Importance of Play in Machine Learning" Externo Pasando Jugo
"QA for AI Systems" Externo Pasando Jugo
"Data & Analytics Governance Strategies for Driving Growth & Preventing Anarchy" Externo Pasando Jugo
"QA for AI Systems" Externo Pasando Jugo
"Making Machine Learning Models Attack-Proof with Adversarial Robustness" Externo Pasando Jugo
"Adventures in Puppy Training with A.I. and a Raspberry Pi" Externo Pasando Jugo
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"Enhance Trust with Machine Learning Model Error Analysis" Externo Pasando Jugo
"QA for AI systems" Externo Pasando Jugo
"Making Machine Learning Models Attack-Proof with Adversarial Robustness" Externo Pasando Jugo
"How XAI will quietly revolutionize AI" Externo Pasando Jugo
"The Data Science Journey: Myths and Tips" Externo Pasando Jugo
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"A.I. is NOT Software!" Externo Pasando Jugo
"Mitigating Bias with the XAI Toolbox" Externo Pasando Jugo
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"How XAI will quietly revolutionize AI" Externo Pasando Jugo
"Adversarial Robustness: How to make Artificial Intelligence models attack-proof!" Externo Pasando Jugo
"Starting your Data science Journey: Myths and Tips" Externo Pasando Jugo
"Making Machine Learning Models Attack-Proof with Adversarial Robustness" Externo Pasando Jugo
"Interpretable Machine Learning" Externo Pasando Jugo
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"Mitigating Bias with the XAI Toolbox" Externo Pasando Jugo
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"What do Planes and Machine Learning have in common? How Interpretable ML can improve decision-making" Externo Pasando Jugo
"XAI is the new AI" Externo Pasando Jugo
"Crop stage forecasting with Machine Learning and Causal Inference" Externo Pasando Jugo
"Interpretable Machine Learning for Model Tuning" Externo Pasando Jugo
"Path to Artificial General Intelligence" Externo Pasando Jugo
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"What do Planes and Machine Learning have in common? How Interpretable ML can improve decision-making" Externo Pasando Jugo
"Why AI Startups need Interpretable Machine Learning?" Externo Pasando Jugo
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"XAI: Learning Fairness with Interpretable Machine" Externo Pasando Jugo
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"Interpretable Multivariate Forecasting with Deep Learning" Externo Pasando Jugo
"Fairness with Interpretable Machine Learning" Externo Pasando Jugo
"The Importance of Interpretable Machine Learning" Externo Pasando Jugo
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"XAI with Monotonic Constraints & Interaction Constraints" Externo Pasando Jugo
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"Ensuring Machine Learning Fairness with Monotonic Constraints" Externo Pasando Jugo
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"Interpretable Machine Learning with Python — What qualities make for a highly rated chocolate bar?" Externo Pasando Jugo
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"Interpretable Machine Learning with Python: Interpreting & Improving Fairness for Recidivism Risk Assessments" Externo Pasando Jugo
"Assistive Augmentation: Lip Reading with AI" Externo Pasando Jugo
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Editorial Externo Pasando Jugo
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Palabras Clave SEO

Nube de Palabras Clave

machine odsc summit learning interpretable video models data workshop talk

Consistencia de las Palabras Clave

Palabra Clave (Keyword) Contenido Título Palabras Claves (Keywords) Descripción Titulos
learning 41
machine 33
talk 32
video 20
data 18

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Dominio : interpretableml.ai

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