Analytics Vidhya

JULY 25, 2022

Introduction Let’s have a simple overview of what Machine Learning is. Machine Learning is the method of teaching computer programs to do a specific task accurately (essentially a prediction) by training a predictive model using various statistical algorithms leveraging data.

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Analytics Vidhya

JUNE 24, 2021

The post Linear predictive models – Part 1 appeared first on Analytics Vidhya. ArticleVideo Book This article was published as a part of the Data Science Blogathon Hello readers. This is part-1 of a comprehensive tutorial on Linear.

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Analytics Vidhya

MAY 24, 2021

The post How to create a Stroke Prediction Model? ArticleVideo Book This article was published as a part of the Data Science Blogathon INTRODUCTION: Stroke is a medical condition that can lead to the. appeared first on Analytics Vidhya.

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Analytics Vidhya

FEBRUARY 4, 2022

classification refers to a predictive modeling problem where a class label is predicted for a given example of […]. The post Loan Approval Prediction Machine Learning appeared first on Analytics Vidhya.

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Analytics Vidhya

MARCH 10, 2021

ArticleVideo Book Introduction Ensembling is nothing but the technique to combine several individual predictive models to come up with the final predictive model. The post Basic Ensemble Techniques in Machine Learning appeared first on Analytics Vidhya.

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Analytics Vidhya

JUNE 29, 2021

ArticleVideo Book Introduction: In this article, I will be implementing a predictive model on Rain Dataset to predict whether or not it will rain. The post Predictive Modelling | Rain Prediction in Australia With Python. appeared first on Analytics Vidhya.

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Analytics Vidhya

JANUARY 12, 2021

Specific to Predictive Models). ArticleVideos This article was published as a part of the Data Science Blogathon. Hello, There Data science has been a vastly growing and improving. The post 5 Important things to Keep in Mind during Data Preprocessing! appeared first on Analytics Vidhya.

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Analytics Vidhya

OCTOBER 12, 2020

Introduction Machine learning is about building a predictive model using historical data. The post Quick Guide to Evaluation Metrics for Supervised and Unsupervised Machine Learning appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.

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KDnuggets

DECEMBER 1, 2023

Image by Author When you are getting started with machine learning, logistic regression is one of the first algorithms you’ll add to your toolbox. It's a Read more »

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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.

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TDAN

AUGUST 17, 2021

If you are planning on using predictive algorithms, such as machine learning or data mining, in your business, then you should be aware that the amount of data collected can grow exponentially over time.

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KDnuggets

JUNE 4, 2024

Master the Fundamentals of Predictive Modeling with Python: An In-Depth Guide to Machine Learning Algorithms and Sci-kit Learn Implementation.

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Dataiku

JANUARY 8, 2024

In the past few years, machine learning (ML) has gone from a discipline restricted to data scientists and engineers to the mainstream of business and analytics.

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KDnuggets

MAY 30, 2022

A machine learning engineer is a programmer proficient in building and designing software to automate predictive models. They have a deeper focus on computer science, compared to data scientists.

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O'Reilly on Data

DECEMBER 12, 2019

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML.

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KDnuggets

AUGUST 31, 2022

When building a predictive model, the quality of the results depends on the data you use. In order to do so, you need to understand the difference between training and testing data in machine learning.

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Analytics Vidhya

DECEMBER 6, 2023

Introduction AI is experiencing a significant shift with the emergence of LLMs like GPT-4, revolutionizing machine understanding and generation of human language. emerges as a formidable tool in predictive modelling, enhancing machine learning with improved efficiency and accuracy. Alongside, xgboost 2.0

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Domino Data Lab

OCTOBER 29, 2021

When you hear words like machine learning (ML) or artificial intelligence (AI), one of the first things that comes to mind is correctly predicting future occurrences or answering difficult questions about the present based on past events. At its core, this is what predictive modeling is all about.

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Dataiku

FEBRUARY 25, 2021

Machine learning has become more and more accessible in the last few years. Thanks to advancements in automated machine learning (AutoML), collaborative AI , and machine learning platforms (like Dataiku ), the use of data — including for predictive modeling — across people of all different job types is on the rise.

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Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g.

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KDnuggets

DECEMBER 23, 2021

Data Science models come with different flavors and techniques — luckily, most advanced models are based on a couple of fundamentals. Which models should you learn when you want to begin a career as Data Scientist?

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Analytics Vidhya

MAY 13, 2022

Introduction on AutoKeras Automated Machine Learning (AutoML) is a computerised way of determining the best combination of data preparation, model, and hyperparameters for a predictive modelling task. The AutoML model aims to automate all actions which require more time, such as algorithm selection, […].

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Analytics Vidhya

JUNE 17, 2023

Data science for marketing is a discipline that combines statistical analysis, machine learning, and predictive modeling to extract meaningful patterns […] The post How to Use Data Science for Marketing? appeared first on Analytics Vidhya.

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Analytics Vidhya

FEBRUARY 25, 2023

Introduction Often while working on predictive modeling, it is a common observation that most of the time model has good accuracy for the training data and lesser accuracy for the test data.

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IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

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Analytics Vidhya

DECEMBER 22, 2022

We have various Machine Learning algorithms to build predictive models. This is the 4th article of the series of data science interview questions. In case you want to revisit the previous ones, tap here. This article will cover all you need to know about boosting algorithms.

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Cloudera

OCTOBER 14, 2020

Not many other industries have such a sophisticated business model that encompasses a culture of streamlined supply chains, predictive maintenance, and unwavering customer satisfaction. Step 1: Using the training data to create a model/classifier. Fig 2: Diagram showing how CML is used to build ML training models.

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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.

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David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

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DataRobot Blog

JANUARY 27, 2019

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. Read More.

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KDnuggets

JANUARY 5, 2022

3 Tools to Track and Visualize the Execution of Your Python Code; 6 Predictive Models Every Beginner Data Scientist Should Master; What Makes Python An Ideal Programming Language For Startups; Alternative Feature Selection Methods in Machine Learning; Explainable Forecasting and Nowcasting with State-of-the-art Deep Neural Networks and Dynamic Factor (..)

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Dataiku

MAY 18, 2022

Machine learning has become more and more accessible in the last few years. Thanks to advancements in automated machine learning (AutoML), collaborative AI , and machine learning platforms (like Dataiku ), the use of data — including for predictive modeling — across people of all different job types is on the rise.

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CIO Business Intelligence

OCTOBER 4, 2022

From delightful consumer experiences to attacking fuel costs and carbon emissions in the global supply chain, real-time data and machine learning (ML) work together to power apps that change industries. more machine learning use casesacross the company. By Bryan Kirschner, Vice President, Strategy at DataStax.

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BizAcuity

APRIL 1, 2023

1] With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions. There are a number of open-source ML platforms like KNIME that can also be leveraged to detect and predict suspicious behavior.

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BizAcuity

JANUARY 18, 2023

With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions. How Machine Learning Helps Detect and Prevent AML. Predictive modeling for flagging suspicious activity.

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Machine Learning Predictive Analytics Predictive Modeling Risk 52

Decision Management Solutions

JANUARY 16, 2020

The Machine Learning Times (previously Predictive Analytics Times) is the only full-scale content portal devoted exclusively to predictive analytics. ” In his article, Eric warns, “Predictive models often fail to launch. In this month’s featured article, Eric Siegel, Ph.D.,

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CIO Business Intelligence

SEPTEMBER 24, 2024

Accelerated adoption of artificial intelligence (AI) is fuelling rapid expansion in both the amount of stored data and the number of processes needed to train and run machine learning models. AI’s impact on cloud costs – managing the challenge AI and machine learning drive up cloud computing costs in various ways.

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