Category Archives: AI

AI-Ready Data Explained with Examples

AI Ready Data Examples

AI-ready data usually refers to data that has been prepared in such a way that it can be effectively used for training artificial intelligence (AI) and generative AI models. In this blog, we will learn about what are the most common attributes of AI-ready data. The following are the top most 5 attributes that AI-ready data would need to have. Data must be: Check out this Gartner paper for further details – We Shape AI, AI shapes us.

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AI-assisted Software Development: Tools & Processes

AI assisted software development

In the rapidly evolving landscape of software development, the integration of artificial intelligence (AI) and generative AI (Gen AI) is not just a luxury but a cornerstone for enhancing software development velocity. This blog delves into the key aspects of Gen AI and AI-assisted software development, presenting actionable takeaways for software leaders, including engineering managers, project managers, product managers, and software engineers. We will look into different tools and related processes that can be enhanced across the entire software development lifecycle. Design & Architect: Crafting the Blueprint Integrate the following tools to speed up the design process while ensuring adherence to best practices, significantly reducing design iteration times. Code & …

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Machine Learning Models Solution Design: Examples

Solution Design for Machine Learning Models - Examples

This blog is crafted for data scientists, machine learning (ML) and software engineers, business analysts / product managers, and anyone involved in the ML project lifecycle, aiming to create a reliable solution design and development strategy / plan for successful AI / machine learning project implementation and value realization. The blog revolves around a series of critical solution design questions, meticulously curated to guide teams from the initial conception of a project to its final deployment and beyond. By addressing each of these solution design questions, teams can ensure that they are not only building a model that is technically proficient but also one that aligns seamlessly with business objectives, …

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Data Science Competitions on Different Online Platforms

Data Science Competitions Online

Data science / Machine Learning is an ever-evolving field, and competitions provide a great way for beginners / practitioners to hone their skills, solve real-world problems, enhance their resumes / CVs and even earn rewards. Here’s a roundup of some notable machine learning / data science / AI competition platforms, each offering unique opportunities. Each of these data science competition platforms offers unique opportunities and challenges, making them ideal for both beginners and expert data scientists at various stages of their careers to learn, compete, and contribute to a wide array of problems.

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Introducing Our New Data Science & AI Trends Page

Launch of Data Science and AI Trends page

We are thrilled to announce the launch of our dedicated Data Science and AI Trends page at VitalFlux.com! This new resource is designed to be a one-stop hub for data scientists, AI enthusiasts, and anyone passionate about staying at the forefront of technological innovation. What You’ll Find Our Data Science & AI Trends page is more than just a collection of articles; it’s a dynamic resource that aggregates the most insightful and current information from various high-impact sources. Here’s a sneak peek at what you can expect: Web Pages Stay informed with our selection of web pages from leading research institutions, tech news outlets, and individual thought leaders in the …

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Linear Regression in Machine Learning: Python Examples

Multiple linear regression example

Last updated: 15th Dec, 2023 In this post, the linear regression concepts in machine learning is explained with multiple real-life examples. Two types of regression models (simple/univariate and multiple/multivariate linear regression) are taken up for sighting examples. In addition, Python code examples are used for demonstrating training of simple linear and multiple linear regression models.  In case you are a machine learning or data science beginner, you may find this post helpful enough. You may also want to check a detailed post – What is Machine Learning? Concepts & Examples. What is Linear Regression? Linear regression is a machine learning concept that is used to build or train the models …

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Random Forest Classifier – Sklearn Python Example

random forest classifier machine learning

Last updated: 13th Dec, 2023 A random forest classifier is an ensemble machine learning method which is used for classification problems, and operates by constructing a multitude of decision trees during training and predicting the class label (of the data). In general, Random Forest is popular due to its high accuracy, robustness to overfitting, ability to handle large datasets with numerous features, and its effectiveness for both classification and regression tasks. Its versatility and ease of use make it widely applicable across various domains. Note that Random Forest and Decision Tree classification algorithms are different, although Random Forest is built upon the concept of Decision Trees. In this post, you …

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Feature Scaling in Machine Learning: Python Examples

While training machine learning models, we come across the need for scaling features in order to have different features contribute to the predictions in an appropriate manner. Without scaling, features with larger numerical ranges can dominate those with smaller ranges, leading to biased or inefficient learning. In this post you will learn about this feature engineering technique namely feature scaling with Python code examples using which you could significantly improve performance of machine learning models. To demonstrate the technique, the models will be trained using Perceptron (single-layer neural network) classifier. What is Feature Scaling? Why is it needed? Feature scaling is a method used to standardize the range of independent variables …

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Confusion Matrix Concepts, Python Code Examples

Confusion Matrix IRIS Dataset Example

The confusion matrix is an essential tool in the field of machine learning and statistics for evaluating the performance of a classification model. It’s particularly useful when dealing with binary or multi-class classification problems.  In this post, you will learn about the confusion matrix with examples and how it could be used as performance metrics for classification models in machine learning. What is Confusion Matrix? A confusion matrix is a table used to describe the performance of a classification model on a set of test data for which the true values are known. It’s most useful when you need to know more about the accuracy of the model than just …

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R-squared in Linear Regression Models: Concepts, Examples

R-squared explained for linear regression model

In linear regression, R-squared (R2) is a measure of how close the data points are to the fitted line. It is also known as the coefficient of determination. Understanding the concept of R-squared is crucial for data scientists as it helps in evaluating the goodness of fit in linear regression models, compare the explanatory power of different models on the same dataset and communicate the performance of their models to stakeholders. In this post, you will learn about the concept of R-Squared in relation to assessing the performance of multilinear regression machine learning model with the help of some real-world examples explained in a simple manner. Before doing a deep dive, …

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Microsoft’s Free Courses: Data Science, Machine Learning, AI

data science for beginners - free course by microsoft

Are you keen on diving into the world of data science, machine learning, or artificial intelligence? Have you been searching for courses that not only teach the fundamentals but are also free and accessible? Look no further! Microsoft has put together three distinct courses that will cater to your interests and ignite your passion for learning. Data Science for Beginners This course offers an ideal starting point for those new to data science, focusing on the basics and guiding through practical exercises. The course would help you demystify the complex world of data, allowing you to make informed decisions in various fields such as business, healthcare, and more. Each lesson …

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Posted in AI, Career Planning, Data Science, Machine Learning, Online Courses. Tagged with , , , .

Hypothesis Testing Steps & Examples

Hypothesis Testing Workflow

Hypothesis testing is a technique that helps scientists, researchers, or for that matter, anyone test the validity of their claims or hypotheses about real-world or real-life events in order to establish new knowledge. Hypothesis testing techniques are often used in statistics and data science to analyze whether the claims about the occurrence of the events are true, whether the results returned by performance metrics of machine learning models are representative of the models or they happened by chance. This blog post will cover some of the key statistical concepts including steps and examples in relation to what is hypothesis testing, how to formulate them and how to use them in …

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7 Free MIT AI / Machine Learning Courses: Enroll Now!

mit courses on machine learning

Are you eager to dive into the world of machine learning and AI but worried about the costs? Are you fascinated by how data analytics can shape the future of various industries? What if you could access top-notch education from one of the leading institutions in the world, absolutely free? In the next six months, MIT is offering seven upcoming free courses designed to equip you with the knowledge and skills in machine learning, AI, and data analytics. Whether you’re a seasoned professional looking to upskill or a beginner ready to embark on a new journey, these courses provide an incredible opportunity. In this blog, we’ll delve into the details …

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IIT Madras Fellowship in AI for Social Good

IIT Madras AI Fellowship for Social Good

Are you an AI researcher driven by the passion to make a positive impact on society? Do you seek to use your knowledge in machine learning and AI to contribute to real-world issues? Are you intrigued by the idea of joining a leading interdisciplinary research center for data science in India? Then here is the opportunity to discover a unique opportunity that aligns with your aspirations and expertise at the Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), IIT Madras. Apply Now for fellowship program in AI for social good. About RBCDSAI RBCDSAI is one of India’s pre-eminent interdisciplinary research academic centers specializing in Data Science and AI. …

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Posted in AI, Career Planning, Data Science, Ethical AI, Machine Learning, Online Courses. Tagged with , , , .

Exploring Amazon Science Publications: A Quick Guide

Amazon science publications

In the ever-evolving world of technology and research, staying updated with the latest advancements is crucial. Amazon Science Publications has emerged as a treasure trove for those hungry for knowledge, offering a plethora of articles that span a wide range of topics. Whether you’re an AI / ML researcher, a student, or just a curious mind, this platform has something for everyone. Let’s delve into the vast ocean of articles available on Amazon Science Publications. Research Areas: Tags: Conferences: Journals: Date: Whether you’re looking for the latest articles from 2023 or want to revisit the gems from 2015, Amazon Science Publications has got you covered. With articles spanning from 2015 …

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Loan Eligibility / Approval & Machine Learning: Examples

loan eligibility prediction using machine learning

It is no secret that the loan industry is a multi-billion dollar industry. Lenders make money by charging interest on loans, and borrowers want to get the best loan terms possible. In order to qualify for a loan, borrowers are typically required to provide information about their income, assets, and credit score. This process can be time consuming and frustrating for both lenders and borrowers. In this blog post, we will discuss how AI / machine learning can be used to predict loan eligibility. As data scientists, it is of great importance to understand some of challenges in relation to loan eligibility and how machine learning models can be built …

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