Category Archives: AI
Types of Probability Distributions: Codes, Examples
In this post, you will learn the definition of 25 different types of probability distributions. Probability distributions play an important role in statistics and in many other fields, such as economics, engineering, and finance. They are used to model all sorts of real-world phenomena, from the weather to stock market prices. Before we get into understanding different types of probability distributions, let’s understand some fundamentals. If you are a data scientist, you would like to go through these distributions. This page could also be seen as a cheat sheet for probability distributions. What are Probability Distributions? Probability distributions are a way of describing how likely it is for a random …
AI Product Manager Interview Questions
AI has become such an integral part of our lives that it is important to hire professionals who can help create AI / machine learning products that will be used by many people. These AI product manager interview questions will give you insight into your product manager candidate’s experience, skills, and industry knowledge so that you can get prepared in a better manner before appearing for your next interview as an AI product manager. Check out a detailed interview questions and answers with greater focus on machine learning topics. Before getting into the list of interview questions, lets understand what can be the job description of an AI product manager. …
Building AI-powered Organization & Cultural Traits
Artificial Intelligence (AI) has become an integral part of many organizations’ operations. From customer service to supply chain management, AI is increasingly being used to automate and streamline processes. However, AI can do more than just help you run your business more efficiently; it can also be used to build organizational culture and foster data-driven decision making in general while leveraging analytical tools & techniques. Let’s take a look at how AI-powered organizational and cultural traits can help improve the workplace. The following picture is a summary of cultural traits in AI-driven organization Be Curious The adoption of artificial intelligence (AI) within an organization can enhance curiosity in several ways. …
Challenges for Machine Learning / AI Projects
In this post, you will learn about some of the key challenges in relation to achieving successful AI / machine learning (ML) or Data science projects implementation in a consistent and sustained manner. As AI / ML project stakeholders including senior management stakeholders, data science architects, product managers, etc, you must get a good understanding of what would it take to successfully execute AI / ML projects and create value for the customers and the business. Whether you are building AI / ML products or enabling unique models for your clients in SaaS setup, you will come across most of these challenges. Understanding the Business Problem Many times, the nature …
Most Common Machine Learning Tasks
This article represents some of the most common machine learning tasks that one may come across while trying to solve machine learning problems. Also listed is a set of machine learning methods that could be used to resolve these tasks. Please feel free to comment/suggest if I missed mentioning one or more important points. Also, sorry for the typos. You might want to check out the post on what is machine learning?. Different aspects of machine learning concepts have been explained with the help of examples. Here is an excerpt from the page: Machine learning is about approximating mathematical functions (equations) representing real-world scenarios. These mathematical functions are also referred …
Supply chain management & Machine Learning
As supply chains become more complex, businesses are looking for new ways to optimize and automate their supply chain operations. One area that is seeing a lot of growth is the use of artificial intelligence (AI) and machine learning in supply chain management. There are many different applications for these technologies in supply chain management, from forecasting demand to optimizing inventory levels. In this blog post, we will explore some of the most interesting use cases for AI and machine learning in supply chain management. What is supply chain management and what are its key components? Supply chain management is the process of coordinating and controlling the flow of goods, …
Weak Supervised Learning: Concepts & Examples
Supervised learning is a type of machine learning algorithm that uses a labeled dataset to learn and generalize from. The labels act as supervisors, providing the algorithm with feedback so it can learn to map input data to the correct output labels. In this blog post, we’ll be focusing on weak supervised learning, a subset of supervised learning that uses only partially labeled or unlabeled data. We’ll cover some of the most common weak supervision techniques and provide examples of each. What is Weak Supervised Learning? Weak supervised learning is a type of machine learning where the learner is only given a few labels to work with. Weak supervision is …
Healthcare Claims Processing AI Use Cases
In recent years, artificial intelligence (AI) / machine learning (ML) has begun to revolutionize many industries – and healthcare is no exception. Hospitals and insurance companies are now using AI to automate various tasks in the healthcare claims processing workflow. Claims processing is a complex and time-consuming task that often requires manual intervention. By using AI to automate claims processing, healthcare organizations can reduce costs, improve accuracy, and speed up the claims adjudication process. In this blog post, we will explore some of the most common use cases for healthcare claims processing AI / machine learning. Automated Data Entry One of the most time-consuming tasks in the claims process is …
ESG & AI / Machine Learning Use Cases
Environmental, social, and governance (ESG) factors are a set of standards used to evaluate a company’s performance on issues that have an impact on society and the environment. AI or machine learning can be used to help identify these factors. In this blog post, we will explore some use cases for how AI / machine learning can be used in conjunction with ESG factors. The following is a list of AI use cases related ESG. This list will be updated from time-to-time. Predict ESG ratings using fundamental dataset: Investors (asset managers and asset owners) started to assess companies based on how they handle sustainability issues. To do this assessment, investors …
How to Identify Use Cases for AI / Machine Learning
As artificial intelligence (AI ) and machine learning (ML) solutions and technologies continue to evolve, more and more businesses are looking for ways to incorporate them into their operations to realize a greater business impact. But with so many potential applications, it can be difficult to know where to start. In this blog post, we’ll outline some tips for identifying AI / ML use cases. We’ll also provide a few examples of how AI & machine learning can be used in business settings. So if you’re thinking about adding AI or machine learning to your toolkit, read on! This blog post will be appropriate for product managers, business analysts, data science …
Predicting Customer Churn with Machine Learning
Customer churn, also known as customer attrition, is a major problem for businesses that rely on recurring revenue. Customer churn costs businesses billions of dollars every year, and it’s only getting worse as customers become more and more fickle. In fact, it’s been estimated that the average company loses 10-15% of its customers each year. That number may seem small, but it can have a huge impact on a company’s bottom line. Fortunately, there’s a way to combat churn: by using machine learning to predict which customers are likely to churn. In this blog post, we’ll discuss how customer churn prediction works and why it’s so important. We’ll also provide …
Import or Upload Local File to Google Colab
Google Colab is a powerful tool that allows you to run Python code in the cloud. This can be useful for a variety of tasks, including data analysis and machine learning. One of the lesser known features of Google Colab is that you can also import or upload files stored on your local drive. In this article, we will show you how to read a file from your local drive in Google Colab using a quick code sample. There are a few reasons why you as a data scientist might need to learn how to read files from your local drive in Google Colab. One reason is that you may …
How to Create Pandas Dataframe from Numpy Array
Pandas is a library for data analysis in Python. It offers a wide range of features, including working with missing data, handling time series data, and reading and writing data in different formats. Pandas also provides an efficient way to manipulate and calculate data. One of its key features is the Pandas DataFrame, which is a two-dimensional array with labeled rows and columns. A DataFrame is a table-like structure that contains columns and rows of data. Creating a Pandas DataFrame from a NumPy array is simple. In this post, you will get a code sample for creating a Pandas Dataframe using a Numpy array with Python programming. Step 1: Load …
Knowledge Graph Concepts & Machine Learning: Examples
Knowledge graphs and machine learning are two important tools for understanding and making decisions in business. Knowledge graphs can be used to understand and model complex concepts, while machine learning is a process by which computers learn from data, without being explicitly programmed. Together, these two tools can be used to make better decisions in business by understanding the relationships between data points. In this blog, you will learn about the basics of knowledge graphs and machine learning, and how they can be used to improve decision making in business. What is a Knowledge Graph & how they can are used? A knowledge graph is a collection of data that …
AI / Machine learning (ML) Model Governance Framework
AI / Machine learning (ML) based solutions / applications have become increasingly important in business and industry. However, with the power to make decisions that can impact people’s lives comes a responsibility to use those tools ethically and responsibly. The machine learning model governance framework is designed to help businesses do just that. In this blog, you will learn about the AI / Machine Learning Model Governance framework, its benefits, and how you can implement it in your organization. What is AI / Machine learning (ML) model governance and why its important? Machine learning model governance is a set of process and related tools & frameworks that the businesses need …
Data-centric vs Model-centric AI: Concepts, Examples
There is a lot of discussion around AI and which approach is better: model-centric or data-centric. In this blog post, we will explore both approaches and give examples of each. We will also discuss the benefits and drawbacks of each approach. By the end of this post, you will have a better understanding of both AI approaches and be able to decide which one is right for your business! As product managers and data science architects, you should be knowledgeable about both of these AI approaches so that you can make informed decisions about the products and services you build. Model-centric approach to AI Model-centric approach to AI is about …
I found it very helpful. However the differences are not too understandable for me