What are model governance and model operations?

O'Reilly on Data

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. We are also beginning to see researchers share sample code written in popular open source libraries, and some even share pre-trained models. Model development.

A Comprehensive Guide to Build your own Language Model in Python!

Analytics Vidhya

Overview Language models are a crucial component in the Natural Language Processing (NLP) journey These language models power all the popular NLP applications we. The post A Comprehensive Guide to Build your own Language Model in Python!

Proposals for model vulnerability and security

O'Reilly on Data

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks.

11 Important Model Evaluation Metrics for Machine Learning Everyone should know

Analytics Vidhya

Overview Evaluating a model is a core part of building an effective machine learning model There are several evaluation metrics, like confusion matrix, cross-validation, The post 11 Important Model Evaluation Metrics for Machine Learning Everyone should know appeared first on Analytics Vidhya.

Learn how to Build your own Speech-to-Text Model (using Python)

Analytics Vidhya

Overview Learn how to build your very own speech-to-text model using Python in this article The ability to weave deep learning skills with NLP. The post Learn how to Build your own Speech-to-Text Model (using Python) appeared first on Analytics Vidhya. NLP Python convert speech to text speech recognition speech recognition model Speech to text speech to text model

Generative and Analytical Models for Data Analysis

Simply Statistics

Another, more informal, way that I like to think about these approaches is as the “biological” model and the “physician” model. Generative Model. This model is useful for understanding the “biological process”, i.e. the underlying mechanisms for how data analyses are created, sometimes referred to as “statistical thinking”. Analytical Model. In other words, there is no outcome on which we can “train our model” for data analysis.

Statistical Modelling vs Machine Learning

KDnuggets

At times it may seem Machine Learning can be done these days without a sound statistical background but those people are not really understanding the different nuances. Code written to make it easier does not negate the need for an in-depth understanding of the problem.

Build your First Multi-Label Image Classification Model in Python

Analytics Vidhya

The post Build your First Multi-Label Image Classification Model in Python appeared first on Analytics Vidhya. Introduction Are you working with image data? There are so many things we can do using computer vision algorithms: Object detection Image segmentation Image. Computer Vision Deep Learning Python deep learning Image Classification multi-label classification python

How do Transformers Work in NLP? A Guide to the Latest State-of-the-Art Models

Analytics Vidhya

Overview The Transformer model in NLP has truly changed the way we work with text data Transformer is behind the recent NLP developments, including. A Guide to the Latest State-of-the-Art Models appeared first on Analytics Vidhya.

Business Architecture and Process Modeling for Digital Transformation

erwin

At a fundamental level, digital transformation is about further synthesizing an organization’s operations and technology, so involving business architecture and process modeling is a best practice organizations cannot ignore. Business Architecture and Process Modeling.

Build a Machine Learning Model in your Browser using TensorFlow.js and Python

Analytics Vidhya

Overview TensorFlow.js (deeplearn.js) enables us to build machine learning and deep learning models right in our browser without needing any complex installation steps There. The post Build a Machine Learning Model in your Browser using TensorFlow.js

Why it’s hard to design fair machine learning models

O'Reilly on Data

They recently wrote a survey paper, “A Critical Review of Fair Machine Learning,” where they carefully examined the standard statistical tools used to check for fairness in machine learning models. Continue reading Why it’s hard to design fair machine learning models

Developing a Web Application for a Machine Learning Model

DataFloq

This post describes developing a web application for a machine learning model and deploying it so that it can be accessed by anyone. The steps involved are as follows: Creating a simple model that can be deployed to the web, where users can input variables to get predictions.

Decision Modeling for Analytics Translators/Interpreters/Storytellers

Decision Management Solutions

By showing how the model works, showing how model outcomes align with the desired business outcomes, they build trust, and improve the odds of success. I would add one new one – decision modeling. Decision modeling is an analysis technique that allows you to capture the structure of a decision-making approach. For any repeatable decision – a decision made more than once following a defined approach – a decision model can be defined. Decision Modeling DMN

Measure Twice, Cut Once: How the Right Data Modeling Tool Drives Business Value

erwin

The need for an effective data modeling tool is more significant than ever. For decades, data modeling has provided the optimal way to design and deploy new relational databases with high-quality data sources and support application development.

Specialized tools for machine learning development and model governance are becoming essential

O'Reilly on Data

Model packaging: companies are using MLflow to incorporate custom logic and dependencies as part of a model’s package abstraction before deploying it to their production environment (example: a recommendation system might be programmed to not display certain images to minors).

Business Process Modeling Use Cases and Definition

erwin

What is business process modeling (BPM)? But a theoretical understanding of business process modeling will only get you so far. The following use cases demonstrate the benefits of business process modeling in real life. Business Process Modeling Use Cases.

Common Data Modeling Mistakes and Their Impact

TDAN

Although data modeling has been around for over 30 years, it ranks among the top areas from which database application problems arise. Today’s data modeling […].

Easily Deploy Deep Learning Models in Production

KDnuggets

Getting trained neural networks to be deployed in applications and services can pose challenges for infrastructure managers. Challenges like multiple frameworks, underutilized infrastructure and lack of standard implementations can even cause AI projects to fail. This blog explores how to navigate these challenges. 2019 Aug News Deep Learning Deployment GPU Inference NVIDIA

Data Modeling Pulls it All Together for the Business!

Smarten

Predictive Modeling allows users to test theories and hypotheses and develop the best strategy. Smarten Advanced Data Discovery Advanced Analytics Natural Language Processing Predictive Analysis Tools Predictive Analytics Predictive Modeling

Start Modeling Data – Data Modeling 101

The Data School

This is a quick introduction to using DBT and Bigquery to model data

How to Understand a DataRobot Model [eBook]

DataRobot

Model interpretability is about ensuring humans can easily understand the models and how decisions are made, because trust in AI can ultimately only be achieved when people can align AI behavior with their organization’s business rules, goals, and values.

Assisted Predictive Modeling

Smarten

Create Citizen Data Scientists with Assisted Predictive Modeling! You need Assisted Predictive Modeling (Plug n’ Play Predictive Analysis with auto-suggestions and recommendations).

CECL Model Alternatives

Perficient Data & Analytics

Since there is no single prescribed method of calculating credit loss under CECL, a variety of models have thus far emerged in the industry to address the requirement, each with its own advantages and downsides. Some of the models that have emerged include: Discounted cash flow analysis: In one of the most widely used models in current practice, the discounted cash flows are calculated using the present value of expected future cash flows discounted at the loan’s effective interest rate.

The trinity of errors in financial models: An introductory analysis using TensorFlow Probability

O'Reilly on Data

An exploration of three types of errors inherent in all financial models. At Hedged Capital , an AI-first financial trading and advisory firm, we use probabilistic models to trade the financial markets. All financial models are wrong. The trinity of modeling errors.

Assisted Predictive Modeling for Business Users!

Smarten

How Can I Leverage Assisted Predictive Modeling to Benefit My Business? Some people hear the term ‘assisted predictive modeling’ and their eyes cross. Explore Assisted Predictive Modeling and find out how it can benefit your organization.

Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models

Occam's Razor

than multi-channel attribution modeling. By the time you are done with this post you'll have complete knowledge of what's ugly and bad when it comes to attribution modeling. You'll know how to use the good model, even if it is far from perfect.

Assisted Predictive Modeling for All Users!

Smarten

There are a myriad of predictive analytics techniques and predictive modeling algorithms and you can’t expect your business users to understand and use them. Predictive Analytics Techniques That Are Easy Enough for Business Users!

DataHack Radio #20: Building Interpretable Machine Learning Models with Christoph Molnar

Analytics Vidhya

Introduction How do we build interpretable machine learning models? Or, in other words, how do we build trust in the models we design? The post DataHack Radio #20: Building Interpretable Machine Learning Models with Christoph Molnar appeared first on Analytics Vidhya. Podcast data science podcast DataHack Radio machine learning

What’s Business Process Modeling Got to Do with It? – Choosing A BPM Tool

erwin

With business process modeling (BPM) being a key component of data governance , choosing a BPM tool is part of a dilemma many businesses either have or will soon face. Understanding the typical use cases for business process modeling is the first step.

Quick Tips on How to Sell Your Data Science Model

Perficient Data & Analytics

During a five-week IBM training program, I learned a few things about how to sell data science models that I’d like to share it with you. The ability to sell your model is as crucial as the aforementioned skills. Quick Tips for Selling Your Data Science Model.

Four Steps to Take After Training Your Model: Realizing the Value of Machine Learning

DataRobot

So, you have successfully trained a machine learning model after choosing the best algorithm and high-quality training data. Time to celebrate, right? Not quite! Partner Blog

Model Interpretability with TCAV (Testing with Concept Activation Vectors)

Domino Data Lab

What if there was a way to quantitatively measure whether your machine learning (ML) model reflects specific domain expertise or potential bias? This Domino Data Science Field Note provides some distilled insights about TCAV, an interpretability method that allows researchers to understand and quantitatively measure the high-level concepts their neural network models are using for prediction, “even if the concept was not part of the training” ( Kim Slide 33 ).

Machine Learning Data Prep Tips for Time Series Models

Jen Underwood

In my previous articles Predictive Model Data Prep: An Art and Science and Data Prep Essentials for Automated Machine Learning, I shared foundational data preparation tips to help you successfully. by Jen Underwood.

Assisted Predictive Modeling for Simple Business Analytics!

Smarten

Just Simple, Assisted Predictive Modeling for Every Business User! And, with Assisted Predictive Modeling , you can make these tasks even easier. Contact Us to find out how Assisted Predictive Modeling can help your business succeed. No Guesswork!

Digital Marketing and Measurement Model

Occam's Razor

Winners, well before they think data or tool, have a well structured Digital Marketing & Measurement Model. I've developed the Digital Marketing & Measurement Model as a simple, structured, five step process to infuse this much needed thinking.

Assisted Predictive Modeling and Analytics for Everyone

Smarten

Conversation Starters Smarten Advanced Data Discovery Assisted Predictive Modeling Plug n’ Play Predictive Analysis Predictive Analysis Predictive Analysis Software Predictive Analysis Tools Predictive Analytics Software Predictive Analytics Tool Predictive Modeling

Multi-Channel Attribution: Definitions, Models and a Reality Check

Occam's Razor

And as if that was not enough, :), I'll close the post with my thoughts on digital marketing attribution models. Almost all current, hot and heavy, literature on the topic of attribution modeling does not cover MCA-O2S. Multi-Channel Attribution Models. Media Mix Models.

Using Smarten’s Assisted Predictive Modeling in the FMCG industry

Smarten

This is a video of a presentation which outlines how a predictive analytics model can be set up for the sales department of a consumer product company.

Assisted Predictive Modeling Guide Users Through the Maze

Smarten

What is Assisted Predictive Modeling? Assisted Predictive Modeling is a great way to provide support for your users and your organization. Anything that can help your business users to understand, interpret and analyze data is a help!