Author Archives: Ajitesh Kumar

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. For latest updates and blogs, follow us on Twitter. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking

Tensor Explained with Python Numpy Examples

Tensors are a hot topic in the world of data science and machine learning. But what are tensors, and why are they so important? In this post, we will explain the concepts of Tensor using Python Numpy examples with the help of simple explanation. We will also discuss some of the ways that tensors can be used in data science and machine learning. When starting to learn deep learning, you must get a good understanding of the data structure namely tensor as it is used widely as the basic data structure in frameworks such as tensorflow, PyTorch, Keras etc. Stay tuned for more information on tensors! What are tensors, and why are …

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Posted in Data Science, Deep Learning, Machine Learning, Python. Tagged with , , .

Supply chain management & AI / Machine Learning

supply chain management and AI and Machine Learning use cases

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, …

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Posted in AI, Machine Learning, Supply chain management. Tagged with , , .

Supplier Relationship Management & Machine Learning / AI

supplier relationship management machine learning

Supplier relationship management (SRM) is the process of managing supplier relationships to develop and maintain a strategic procurement partnership. SRM includes focus areas such as supplier selection, procurement strategy development, procurement negotiation, and performance measurement and improvement. SRM has been around for over 20 years but we are now seeing new technologies such as machine learning come into play. What exactly does advanced analytics such as artificial intelligence (AI) / machine learning (ML) have to do with SRM? And how will AI/ML technologies transform procurement? What are some real-world machine learning use cases related to supplier relationships management? What are a few SRM KPIs/metrics which can be tracked by leveraging …

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Posted in Artificial Intelligence, Data Science, Machine Learning, Procurement. Tagged with , , .

Cohen Kappa Score Python Example: Machine Learning

Cohen Kappa Score Confusion Matrix

Cohen’s Kappa Score is a statistic used to measure the performance of machine learning classification models. In this blog post, we will discuss what Cohen’s Kappa Score is and Python code example representing how to calculate Kappa score using Python. We will also provide a code example so that you can see how it works! What is Cohen’s Kappa Score or Coefficient? Cohen’s Kappa Score, also known as the Kappa Coefficient, is a statistical measure of inter-rater agreement for categorical data. Cohen’s Kappa Coefficient is named after statistician Jacob Cohen, who developed the metric in 1960.   It is generally used in situations where there are two raters, but it …

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Posted in Data Science, Machine Learning, Python. Tagged with , , .

Feedforward Neural Network Python Example

A feedforward neural network, also known as a multi-layer perceptron, is composed of layers of neurons that propagate information forward. In this post, you will learn about the concepts of feedforward neural network along with Python code example. We will start by discussing what a feedforward neural network is and why they are used. We will then walk through how to code a feedforward neural network in Python. In order to get good understanding on deep learning concepts, it is of utmost importance to learn the concepts behind feed forward neural network in a clear manner. Feed forward neural network learns the weights based on backpropagation algorithm which will be discussed …

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Posted in Data Science.

Artificial Intelligence (AI) for Telemedicine: Use cases, Challenges

In this post, you will learn about different artificial intelligence (AI) use cases of Telemedicine / Telehealth including some of key implementation challenges pertaining to AI / machine learning. In case you are working in the field of data science / machine learning, you may want to go through some of the challenges, primarily AI related, which is thrown in Telemedicine domain due to upsurge in need of reliable Telemedicine services. What is Telemedicine? Telemedicine is the remote delivery of healthcare services, using digital communication technologies. It has the potential to improve access to healthcare, especially in remote or underserved communities. It can be used for a variety of purposes, including …

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Posted in AI, Data Science, Healthcare, Machine Learning, Telemedicine. Tagged with , , , , , .

Digital Healthcare Technology & Innovations: Examples

digital health technology and innovations

Digital healthcare technology is making waves in the medical community. It has the potential to change the way we approach healthcare, and it is already starting to revolutionize the way patients are treated. In this blog post, we will explore some of the most exciting digital healthcare technologies including AI / machine learning & blockchain based applications, initiatives and innovations. We will also take a look at some real-world examples of how these technologies are being used to improve patient care. Digital health refers to the use of digital technology to improve the delivery of healthcare services. Connected health (also known as i-health) is a term that encompasses all digital …

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Posted in AI, BlockChain, digital transformation, Healthcare, Machine Learning. Tagged with , , .

Scatter plot Matplotlib Python Example

Scatter Plot representing Two Classes

If you’re a data scientist, data analyst or a Python programmer, data visualization is key part of your job. And what better way to visualize all that juicy data than with a scatter plot? Matplotlib is your trusty Python library for creating charts and graphs, and in this blog we’ll show you how to use it to create beautiful scatter plots using examples and with the help of Matplotlib library. So dig into your data set, get coding, and see what insights you can uncover!  What is a Scatter Plot? A scatter plot is a type of data visualization that is used to show the relationship between two variables. Scatter …

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Posted in AI, Data Science, Machine Learning. Tagged with , , .

Why AI & Machine Learning Projects Fail?

AI and machine learning solution approaches

AI / Machine Learning and data science projects are becoming increasingly popular for businesses of all sizes. Every organization is trying to leverage AI to further automate their business processes and gain competitive edge by delivering innovative solutions to their customers. However, many of these AI & machine learning projects fail due to various different reasons. In this blog post, we will discuss some of the reasons why AI / Machine Learning / Data Science projects fail, and how you can avoid them. The following are some of the reasons why AI / Machine learning projects fail: Lack of understanding of business problems / opportunities Ineffective solution design approaches Lack …

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Posted in AI, Data Science, Machine Learning.

Weight Decay in Machine Learning: Concepts

Weight decay machine learning neural networks

Weight decay is a popular technique in machine learning that helps to improve the accuracy of predictions. In this post, we’ll take a closer look at what weight decay is and how it works. We’ll also discuss some of the benefits of using weight decay and explore some possible applications. As data scientists, it is important to learn about concepts of weight decay as it helps in building machine learning models having higher generalization performance. Stay tuned! What is weight decay and how does it work? Weight decay is a regularization technique that is used to regularize the size of the weights of certain parameters in machine learning models. Weight …

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Posted in Data Science, Machine Learning. Tagged with , .

K-Fold Cross Validation – Python Example

K-Fold Cross Validation Concepts with Python and Sklearn Code Example

In this post, you will learn about K-fold Cross-Validation concepts with Python code examples. K-fold cross-validation is a data splitting technique that can be implemented with k > 1 folds. K-Fold Cross Validation is also known as k-cross, k-fold cross-validation, k-fold CV, and k-folds. The k-fold cross-validation technique can be implemented easily using Python with scikit learn (Sklearn) package which provides an easy way to calculate k-fold cross-validation models.  It is important to learn the concepts of cross-validation concepts in order to perform model tuning with the end goal to choose a model which has a high generalization performance. As a data scientist / machine learning Engineer, you must have a good …

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Posted in Data Science, Machine Learning, Python. Tagged with , , , .

Model Complexity & Overfitting in Machine Learning

model complexity vs model overfitting vs model accuracy

In machine learning, model complexity and overfitting are related in a manner that the model overfitting is a problem that can occur when a model is too complex due to different reasons. This can cause the model to fit the noise in the data rather than the underlying pattern. As a result, the model will perform poorly when applied to new and unseen data. In this blog post, we will discuss what model complexity is and how you can avoid overfitting in your machine learning models by handling the model complexity. As data scientists, it is of utmost importance to understand the concepts related to model complexity and how it …

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Posted in Data Science, Machine Learning. Tagged with , .

Activation Functions in Neural Networks: Concepts

The activation functions are critical to understanding neural networks. It is important to use the activation function in order to train the neural network. There are many activation functions available for data scientists to choose from, so it can be difficult to choose which activation function will work best for their needs. In this blog post, we look at different activation functions and provide examples of when they should be used in different types of neural networks. If you are starting on deep learning and wanted to know about different types of activation functions, you may want to bookmark this page for quicker access in the future. What are activation …

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Posted in Deep Learning, Machine Learning. Tagged with , , .

Purpose of Dashboard: Advantages & Disadvantages

Dashboard - advantages and disadvantages

A dashboard is a visual representation of the most important information needed to achieve a goal. Dashboards form an integral part of analytical solutions. As the demand for data analytics continues to grow, dashboards are well-positioned to become one of the most essential tools in any business toolkit. It can provide an overview of what is happening in your business and help you make better decisions. While there are many advantages to using a dashboard, there are also some disadvantages that you should be aware of. In this blog post, we will discuss the purpose of the dashboard and its advantages and disadvantages. As a product manager/business analyst and data …

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Posted in Data analytics. Tagged with .

How to Identify AI / Machine Learning Use Cases

identify ai and machine learning use cases

As AI and machine learning 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 and machine learning 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 architects, data …

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Posted in AI, Data analytics, Machine Learning, Product Management. Tagged with , , .

Softmax Regression Explained with Python Example

In this post, you will learn about the concepts of what is Softmax regression/function with Python code examples and why do we need them? As data scientist/machine learning enthusiasts, it is very important to understand the concepts of Softmax regression as it helps in understanding the algorithms such as neural networks, multinomial logistic regression, etc in a better manner. Note that the Softmax function is used in various multiclass classification machine learning algorithms such as multinomial logistic regression (thus, also called softmax regression), neural networks, etc. Before getting into the concepts of softmax regression, let’s understand what is softmax function. What’s Softmax function? Simply speaking, the Softmax function converts raw …

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Posted in Data Science, Machine Learning. Tagged with , , .