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The post Regime Shift Models – A Fascinating Use Case of Time Series Modeling appeared first on Analytics Vidhya. Python Time Series regime shift modeling regime shift models stock market prediction time series pythonThis article is written by Sonam Srivastava. She is one of the eminent speakers at DataHack Summit 2019, where she will be talking about. MORE
Overview Gaussian Mixture Models are a powerful clustering algorithm Understand how Gaussian Mixture Models work and how to implement them in Python We’ll also. The post Build Better and Accurate Clusters with Gaussian Mixture Models appeared first on Analytics Vidhya. MORE
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. MORE
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. MORE
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. MORE
Model interpretability continues to spark public discourse among industry. We have covered model interpretability previously, including a proposed definition of machine learning (ML) interpretability. While we offer a platform-as-a-service , where industry can use their choice of languages, tools, and infra to support model-driven workflows, we cover practical techniques and research in this blog to help industry make their own assessments. Model Interpretability with TCAV. MORE
The Case for Building Trust in Machine Learning Models There are approximately 1.2 The post 6 Python Libraries to Interpret Machine Learning Models and Build Trust appeared first on Analytics Vidhya. Data Visualization Intermediate Libraries Listicle Machine Learning Python build trust in machine learning ELI5 interpret machine learning models LIME machine learning machine learning algorithms machine learning interpretability SHAP understand machine learning algorithms MORE
The post Build your own Vehicle Detection Model using OpenCV and Python appeared first on Analytics Vidhya. Overview Excited by the idea of smart cities? You’ll love this tutorial on building your own vehicle detection system We’ll first understand how to. MORE
The post Top 6 Open Source Pretrained Models for Text Classification you should use appeared first on Analytics Vidhya. Introduction We are standing at the intersection of language and machines. I’m fascinated by this topic. Can a machine write as well as Shakespeare? MORE
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 MORE
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 MORE
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. MORE
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 MORE
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 MORE
With the ongoing disruption of our lives, communities, and businesses from the COVID-19 pandemic, predictions from existing machine learning models trained prior to the pandemic become less reliable. The world is going through extremely turbulent times. MORE
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? MORE
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. MORE
Once you have deployed your machine learning model into production, differences in real-world data will result in model drift. This guide defines model drift and how to identify it, and includes approaches to enable model training. MORE
What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. In the modern context, data modeling is a function of data governance. MORE
An integrated data foundation allows data science models to be more accurate, actionable and engage more customers. Find out how your model can positively impact your bottom line MORE
Overview Interpretable machine learning is a critical concept every data scientist should be aware of How can you build interpretable machine learning models? MORE
Technical teams charged with maintaining and executing these processes require detailed tasks, and business process modeling is integral to their documentation. erwin’s Evolve software is integral to modeling process flow requirements, but what about the technology side of the equation? The erwin disaster recovery model answers these questions by capturing and displaying the relevant data. So what does an erwin disaster recovery model show? MORE
Data modeling and database design is an in-demand career path, and database design is a crucial skill set that experienced DBAs must possess. MORE
Overview Deploying your machine learning model is a key aspect of every ML project Learn how to use Flask to deploy a machine learning. The post How to Deploy Machine Learning Models using Flask (with Code!) MORE
There are three different types of data models: conceptual, logical and physical, and each has a specific purpose. Conceptual Data Models: High-level, static business structures and concepts. Logical Data Models: Entity types, data attributes and relationships between entities. MORE
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. MORE
The post Build Your First Text Classification model using PyTorch appeared first on Analytics Vidhya. Overview Learn how to perform text classification using PyTorch Understand the key points involved while solving text classification Learn to use Pack Padding feature. MORE
Overview This article dives into the key question – is class sensitivity in a classification problem model-dependent? The post Is Class Sensitivity Model Dependent? MORE
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! MORE
Enterprise architecture (EA) and business process (BP) modeling tools are evolving at a rapid pace. Regulatory Compliance Through Enterprise Architecture & Business Process Modeling Software. The Advantages of Enterprise Architecture & Business Process Modeling from erwin. MORE
Can you fool your deep learning model? What does lying to your deep learning model even entail? The post Can you Lie to your Deep Learning Model? This question we’re sure most of you. appeared first on Analytics Vidhya. MORE
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 MORE
Use PyCaret to Build your Machine Learning Model in Seconds appeared first on Analytics Vidhya. Data Visualization Libraries Programming Python machine learning model pycaret pycaret library pycaret machine learning pycaret model pycaret python python Python library MORE
The post Build your Own Object Detection Model using TensorFlow API appeared first on Analytics Vidhya. The World of Object Detection I love working in the deep learning space. It is, quite frankly, a vast field with a plethora of. MORE
For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Today’s data modeling is not your father’s data modeling software. erwin Data Modeler: Where the Magic Happens. MORE
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. MORE
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. MORE
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. MORE
Learn about deploying deep learning models using TensorFlow Serving How to handle post-deployment challenges like swapping between different versions of models using TensorFlow Serving. The post TensorFlow Serving: Deploying Deep Learning Models Just Got Easier! MORE
2020 Mar Tutorials, Overviews Decision Boundaries Machine Learning Modeling R MORE
Overview Generative models and GANs are at the core of recent progress in computer vision applications This article will introduce you to the world. The post What are Generative Models and GANs? MORE
You can learn a vital new skill – Decision Requirements Modeling – from the comfort of your home FOR FREE! We are going to take some of our popular online training materials and provide a FREE 2-hour introduction to modeling decision requirements. This session will focus on the most valuable feature of decision modeling, its power to accurate capture how business people want a decision to be made. MORE
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. MORE
Modeling Related Topics 
Analytics Vidhya
APRIL 29, 2020
Overview Deploying your machine learning model is a key aspect of every ML project Learn how to use Flask to deploy a machine learning. The post How to Deploy Machine Learning Models using Flask (with Code!)
Analytics Vidhya
MAY 18, 2020
Use PyCaret to Build your Machine Learning Model in Seconds appeared first on Analytics Vidhya. Data Visualization Libraries Programming Python machine learning model pycaret pycaret library pycaret machine learning pycaret model pycaret python python Python library
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Analytics Vidhya
MARCH 2, 2020
Learn about deploying deep learning models using TensorFlow Serving How to handle post-deployment challenges like swapping between different versions of models using TensorFlow Serving. The post TensorFlow Serving: Deploying Deep Learning Models Just Got Easier!
Analytics Vidhya
MARCH 29, 2020
Can you fool your deep learning model? What does lying to your deep learning model even entail? The post Can you Lie to your Deep Learning Model? This question we’re sure most of you. appeared first on Analytics Vidhya.
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Analytics Vidhya
MARCH 17, 2020
The post Top 6 Open Source Pretrained Models for Text Classification you should use appeared first on Analytics Vidhya. Introduction We are standing at the intersection of language and machines. I’m fascinated by this topic. Can a machine write as well as Shakespeare?
O'Reilly on Data
JUNE 19, 2019
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.
|
erwin
JANUARY 24, 2020
There are three different types of data models: conceptual, logical and physical, and each has a specific purpose. Conceptual Data Models: High-level, static business structures and concepts. Logical Data Models: Entity types, data attributes and relationships between entities.
Analytics Vidhya
OCTOBER 30, 2019
Overview Gaussian Mixture Models are a powerful clustering algorithm Understand how Gaussian Mixture Models work and how to implement them in Python We’ll also. The post Build Better and Accurate Clusters with Gaussian Mixture Models appeared first on Analytics Vidhya.
Analytics Vidhya
AUGUST 7, 2019
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!
Analytics Vidhya
APRIL 6, 2020
The post Build your Own Object Detection Model using TensorFlow API appeared first on Analytics Vidhya. The World of Object Detection I love working in the deep learning space. It is, quite frankly, a vast field with a plethora of.
Analytics Vidhya
OCTOBER 22, 2019
The post Regime Shift Models – A Fascinating Use Case of Time Series Modeling appeared first on Analytics Vidhya. Python Time Series regime shift modeling regime shift models stock market prediction time series pythonThis article is written by Sonam Srivastava. She is one of the eminent speakers at DataHack Summit 2019, where she will be talking about.
O'Reilly on Data
MARCH 20, 2019
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.
|
|
Analytics Vidhya
JULY 14, 2019
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
Analytics Vidhya
AUGUST 5, 2019
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.
Analytics Vidhya
MARCH 24, 2020
The Case for Building Trust in Machine Learning Models There are approximately 1.2 The post 6 Python Libraries to Interpret Machine Learning Models and Build Trust appeared first on Analytics Vidhya. Data Visualization Intermediate Libraries Listicle Machine Learning Python build trust in machine learning ELI5 interpret machine learning models LIME machine learning machine learning algorithms machine learning interpretability SHAP understand machine learning algorithms
erwin
JANUARY 9, 2020
For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Today’s data modeling is not your father’s data modeling software. erwin Data Modeler: Where the Magic Happens.
TDAN
SEPTEMBER 17, 2019
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?
Analytics Vidhya
OCTOBER 15, 2019
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
Analytics Vidhya
OCTOBER 6, 2019
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.
Analytics Vidhya
JANUARY 27, 2020
The post Build Your First Text Classification model using PyTorch appeared first on Analytics Vidhya. Overview Learn how to perform text classification using PyTorch Understand the key points involved while solving text classification Learn to use Pack Padding feature.
Analytics Vidhya
APRIL 20, 2020
The post Build your own Vehicle Detection Model using OpenCV and Python appeared first on Analytics Vidhya. Overview Excited by the idea of smart cities? You’ll love this tutorial on building your own vehicle detection system We’ll first understand how to.
Analytics Vidhya
JANUARY 12, 2020
Overview Generative models and GANs are at the core of recent progress in computer vision applications This article will introduce you to the world. The post What are Generative Models and GANs?
erwin
JANUARY 17, 2020
What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. In the modern context, data modeling is a function of data governance.
Teradata
NOVEMBER 11, 2019
An integrated data foundation allows data science models to be more accurate, actionable and engage more customers. Find out how your model can positively impact your bottom line
KDnuggets
MARCH 13, 2020
2020 Mar Tutorials, Overviews Decision Boundaries Machine Learning Modeling R
DataRobot
APRIL 10, 2020
With the ongoing disruption of our lives, communities, and businesses from the COVID-19 pandemic, predictions from existing machine learning models trained prior to the pandemic become less reliable. The world is going through extremely turbulent times.
Decision Management Solutions
MARCH 25, 2020
You can learn a vital new skill – Decision Requirements Modeling – from the comfort of your home FOR FREE! We are going to take some of our popular online training materials and provide a FREE 2-hour introduction to modeling decision requirements. This session will focus on the most valuable feature of decision modeling, its power to accurate capture how business people want a decision to be made.
Analytics Vidhya
MARCH 17, 2019
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.
Analytics Vidhya
FEBRUARY 13, 2020
Overview This article dives into the key question – is class sensitivity in a classification problem model-dependent? The post Is Class Sensitivity Model Dependent?
Analytics Vidhya
AUGUST 25, 2019
Overview Interpretable machine learning is a critical concept every data scientist should be aware of How can you build interpretable machine learning models?
Domino Data Lab
OCTOBER 16, 2019
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.
erwin
MARCH 24, 2020
Technical teams charged with maintaining and executing these processes require detailed tasks, and business process modeling is integral to their documentation. erwin’s Evolve software is integral to modeling process flow requirements, but what about the technology side of the equation? The erwin disaster recovery model answers these questions by capturing and displaying the relevant data. So what does an erwin disaster recovery model show?
erwin
JULY 11, 2019
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.
Simply Statistics
APRIL 28, 2019
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.
Domino Data Lab
NOVEMBER 14, 2019
Model interpretability continues to spark public discourse among industry. We have covered model interpretability previously, including a proposed definition of machine learning (ML) interpretability. While we offer a platform-as-a-service , where industry can use their choice of languages, tools, and infra to support model-driven workflows, we cover practical techniques and research in this blog to help industry make their own assessments. Model Interpretability with TCAV.
KDnuggets
DECEMBER 16, 2019
Once you have deployed your machine learning model into production, differences in real-world data will result in model drift. This guide defines model drift and how to identify it, and includes approaches to enable model training.
Analytics Vidhya
JUNE 11, 2019
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
KDnuggets
OCTOBER 14, 2019
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
Analytics Vidhya
APRIL 14, 2019
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
erwin
FEBRUARY 20, 2020
Enterprise architecture (EA) and business process (BP) modeling tools are evolving at a rapid pace. Regulatory Compliance Through Enterprise Architecture & Business Process Modeling Software. The Advantages of Enterprise Architecture & Business Process Modeling from erwin.
erwin
JUNE 27, 2019
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.
KDnuggets
AUGUST 14, 2019
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.
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