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!

Build your First Linear Regression Model in Qlik Sense

Analytics Vidhya

The post Build your First Linear Regression Model in Qlik Sense appeared first on Analytics Vidhya. Business Intelligence Data Science linear regression linear regression qlik Predictive modeling python qilkview Qlik Qlik Sense

Deployed your Machine Learning Model? Here’s What you Need to Know About Post-Production Monitoring

Analytics Vidhya

Overview What are the next steps after you’ve deployed your machine learning model? The post Deployed your Machine Learning Model? Data Science deployment machine learning model deployment model monitoringPost-deployment monitoring is a crucial step in any machine learning project. Here’s What you Need to Know About Post-Production Monitoring appeared first on Analytics Vidhya.

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

Choosing a Machine Learning Model

KDnuggets

Selecting the perfect machine learning model is part art and part science. Learn how to review multiple models and pick the best in both competitive and real-world applications. 2019 Oct Opinions Interpretability Kaggle Machine Learning

On Being Model-driven: Metrics and Monitoring

Domino Data Lab

This article covers a couple of key Machine Learning (ML) vital signs to consider when tracking ML models in production to ensure model reliability, consistency and performance in the future. Machine learning models: running wild. The model produced an output.

Conceptual Modeling Requires Conceptual and Critical Thinking

TDAN

I am surprised to see a lot of people jumping straight into logical or even physical modeling and skipping conceptual modeling. Don’t they understand the value of conceptual modeling? Don’t they understand the difference between the various levels of modeling?

Decoding the Black Box: An Important Introduction to Interpretable Machine Learning Models in Python

Analytics Vidhya

Overview Interpretable machine learning is a critical concept every data scientist should be aware of How can you build interpretable machine learning models?

Automate Hyperparameter Tuning for Your Models

KDnuggets

When we create our machine learning models, a common task that falls on us is how to tune them. 2019 Sep Tutorials, Overviews Automated Machine Learning Hyperparameter Machine Learning ModelingSo that brings us to the quintessential question: Can we automate this process?

8 Excellent Pretrained Models to get you Started with Natural Language Processing (NLP)

Analytics Vidhya

The post 8 Excellent Pretrained Models to get you Started with Natural Language Processing (NLP) appeared first on Analytics Vidhya. Deep Learning NLP Python deep learning Natural language processing pretrained models pythonIntroduction Natural Language Processing (NLP) applications have become ubiquitous these days. I seem to stumble across websites and applications regularly that are leveraging NLP.

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 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

Build an Image Classification Model using Convolutional Neural Networks in PyTorch

Analytics Vidhya

Overview A hands-on tutorial to build your own convolutional neural network (CNN) in PyTorch We will be working on an image classification problem – The post Build an Image Classification Model using Convolutional Neural Networks in PyTorch appeared first on Analytics Vidhya.

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

Step-by-Step Deep Learning Tutorial to Build your own Video Classification Model

Analytics Vidhya

The post Step-by-Step Deep Learning Tutorial to Build your own Video Classification Model appeared first on Analytics Vidhya. Overview Learn how you can use computer vision and deep learning techniques to work with video data We will build our own video classification.

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.

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.

Version Control for Data Science: Tracking Machine Learning Models and Datasets

KDnuggets

2019 Sep Tutorials, Overviews Data Science Datasets Machine Learning ModelingI am a Git god, why do I need another version control system for Machine Learning Projects?

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.

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

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.

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.

Webinar: Build auto-adaptive machine learning models with Kubernetes

KDnuggets

This live webinar, Oct 2 2019, will instruct data scientists and machine learning engineers how to build manage and deploy auto-adaptive machine learning models in production.

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).

Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. In the present chapter [excerpt], we cover code that will enable you to create your own word vectors as well as to provide them as an input into a deep learning model.

Exponential Organizations Start with Internal Business Process Modeling

erwin

Strong internal business process modeling and management helps data-driven organizations compete and lead. The Value of Internal Business Process Modeling. Benefits of Internal Business Process Modeling and Management.

Automate Hyperparameter Tuning for your models

MLWhiz

When we create our machine learning models, a common task that falls on us is how to tune them. People end up taking different manual approaches. Some of them work, and some don’t, and a lot of time is spent in anticipation and running the code again and again.

It Really Gives a Kick to Build Models

DataFloq

‘It really gives a kick to build models that are used around the world in the food & agri sector’. Jasper Hommels, head of Rural Modelling. Jasper Hommels (47) is the head of the Rural Modeling project: the development of new credit risk models for Rabobank’s global agricultural loans. He leads an international team of data analysts and modelers. To do that, we need different credit risk models than the ones we use in the Netherlands.

Activation maps for deep learning models in a few lines of code

KDnuggets

We illustrate how to show the activation maps of various layers in a deep CNN model with just a couple of lines of code. 2019 Oct Tutorials, Overviews Architecture Deep Learning Neural Networks Python

Start Modeling Data – Data Modeling 101

The Data School

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

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

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

Upcoming Webinar, Machine Learning Vital Signs: Metrics and Monitoring Models in Production

KDnuggets

In this upcoming webinar on Oct 23 @ 10 AM PT, learn why you should invest time in monitoring your machine learning models, the dangers of not paying attention to how a model’s performance can change over time, metrics you should be gathering for each model and what they tell you, and much more.

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).

Introducing AI Explainability 360: A New Toolkit to Help You Understand what Machine Learning Models are Doing

KDnuggets

Recently, AI researchers from IBM open sourced AI Explainability 360, a new toolkit of state-of-the-art algorithms that support the interpretability and explainability of machine learning models. 2019 Aug Tutorials, Overviews AI Explainability Machine Learning Modeling

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.