# Category Archives: Machine Learning

## What are Sequence Models: Types & Examples

Sequence models are a very common sequence modeling technique in machine learning that is used for analyzing sequence data. This blog post will discuss types of sequence models, their examples, and how they can be used to help with the understanding and analysis of sequences. What is sequence data? Sequence data are the data points which are ordered in the meaningful manner such that earlier data points or observations provide the information about later data points or observations. The time series data is an example of sequence data which can be defined as a sequence of observations where each observation is dependent on the previous one. Sequence data can be …

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## K-Fold Cross Validation – Python Example

In this post, you will learn about K-fold Cross Validation concepts with Python code example. 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 package which provides an easy way to calculate k-fold cross validation models.  It is important to learn the concepts cross validation concepts in order to perform model tuning with an end goal to choose model which has the high generalization performance. As a data scientist / machine learning Engineer, you must …

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## Elbow Method vs Silhouette Score – Which is Better?

In K-means clustering, elbow method and silhouette analysis or score techniques are used to find the number of clusters in a dataset. The elbow method is used to find the “elbow” point, where adding additional data samples does not change cluster membership much. Silhouette score determines whether there are large gaps between each sample and all other samples within the same cluster or across different clusters. In this post, you will learn about these two different methods to use for finding optimal number of clusters in K-means clustering. Selecting optimal number of clusters is key to applying clustering algorithm to the dataset. As a data scientist, knowing these two techniques to find …

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## Different types of Machine Learning: Models / Algorithms

Machine learning is a type of machine intelligence that enables computers to learn and improve without being explicitly programmed. It’s based on the idea that we can build systems which allow our data to do the talking, by finding patterns in vast quantities of information. These machine learning algorithms require different types of machine-learning models trained using different algorithms, depending on what problem they are trying to solve or how accurate an answer needs to be. In this blog post, we will discuss the following four different types of machine learning models / algorithms: Supervised learning Unsupervised learning Semi-supervised learning Reinforcement learning What is supervised learning? Supervised learning is defined …

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## Deep Neural Network Examples from Real-life

The deep neural network (DNN) is an artificial neural network, which has a number of hidden layers and nodes. Deep NN is composed of many interconnected and non-linear processing units that work in parallel to process information more quickly than the traditional neural networks. Deep learning algorithms are used for classification, regression analysis, prediction and other types of tasks. In this blog post, we will present deep neural network examples from the real-world/real-life. Before jumping into examples, you may want to check out some of my following posts on deep neural network: Deep Learning Explained Simply in Layman Terms Neural network explained with perceptron example Perceptron explained with Python example …

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## Free AI / Machine Learning Courses at Alison.com

Are you interested in learning about AI / machine learning / data sicence and looking for free online courses? As per MANUELA M. VELOSO, Herbert A. Simon University Professor at CMU,Machine Learning (ML) is a fascinating field of Artificial Intelligence (AI) research and practice where  we investigate how  computer agents can improve their perception, cognition, and action  with experience. Machine Learning is about machines improving from  data, knowledge, experience, and interaction. Machine Learning  utilizes a variety of techniques to intelligently handle large and complex amounts of  information build upon foundations  in many disciplines, including  statistics, knowledge representation, planning and control, databases, causal inference, computer systems, machine vision, and natural  language …

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## Difference between Supervised & Unsupervised Learning

Supervised and unsupervised learning are two different common types of machine learning tasks that are used to solve many different types of business problems. Supervised learning uses training data with labels to create supervised models, which can be used to predict outcomes for future datasets. Unsupervised learning is a type of machine learning task where the training data is not labeled or categorized in any way. For beginner data scientists, it is very important to get a good understanding of the difference between supervised and unsupervised learning. In this post, we will discuss how supervised and unsupervised algorithms work and what is difference between them. You may want to check …

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## NIT Warangal offers one-week online training on AI, Machine Learning

Are you interested in learning about AI and Machine Learning, or refresing your concepts? NIT Warangal offers one-week online paid training (minimal fees) on AI, Machine Learning. This program is a great opportunity for students to learn about AI & machine learning basics and advanced concepts. It is organized by the Department of Electronics and Communication Engineering & Department of R&D in association with Center of Continuing Education. It will be taught by experience professors who have years of experience in their respective fields. The course will take place between 30th November to 4th December 2021, and it is open to all Faculty/ Research Scholars/Industry professionals/ and other eligible students …

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## ML Engineer vs Data Scientist: Differences & Similarities

In today’s world, ML (machine learning) engineer and Data scientist are two popular job positions. These positions have a lot of overlap but there are also some key differences to be aware of. In this blog post, we will go over the details of ML engineers vs Data scientists so you can decide which one is right for you! What does an ML engineer do? An ML engineer primarily designs and develops machine learning systems. Before getting into the roles & responsibilities of an ML engineer, let’s understand what is a machine learning system. A machine learning system can be defined as a system that comprises of one or more …

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## Real-World Applications of Convolutional Neural Networks

Convolutional neural networks (CNNs) are a type of deep learning algorithm that has been used in a variety of real-world applications. CNNs can be trained to classify images, detect objects in an image, and even predict the next word in a sentence with incredible accuracy. CNNs can also be applied to more complex tasks such as natural language processing (NLP). CNNs are very good at solving classification problems because they’re able to identify patterns within data sets. This blog post will explore some CNN applications and discuss how CNN models can be used to solve real-world problems. Before getting into the details of CNN applications, let’s quickly understand what are …

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## Week Nov1, 2021: Top 3 Machine Learning Tutorial Videos

The field of machine learning is a vast topic and it can be hard to know where to start. In this blog post, we’ll cover the top three free tutorial videos on machine learning from YouTube published this week (Week of Nov 1, 2021). These videos will help you get started with the basics of machine learning & deep learning, introduce you to some popular algorithms in use today, and give you an idea of what’s possible when building a model from scratch.  Build a Machine Learning Project From Scratch with Python and Scikit-learn Let’s say you want to build a machine learning project from scratch. Maybe you’re not sure …

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## Support Vector Machine (SVM) Interview Questions

Support Vector Machine (SVM) is a machine learning algorithm that can be used to classify data. SVM does this by maximizing the margin between two classes, where “margin” refers to the distance from both support vectors. SVM has been applied in many areas of computer science and beyond, including medical diagnosis software for tuberculosis detection, fraud detection systems, and more. This blog post consists of quiz comprising of questions and answers on SVM. This is a practice test (objective questions and answers) that can be useful when preparing for interviews. The questions in this and upcoming practice tests could prove to be useful, primarily, for data scientists or machine learning interns/ …

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## 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 candidate’s experience, skills, and industry knowledge so that you can get prepared in a betterinterma 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. Here are some interview questions that you can get when you are appearing for AI / Machine learning (ML) product manager (PM) job: …

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## Machine Learning Examples from Daily Life

Machine learning is a powerful machine intelligence technique that can be used in a variety of settings to generate data insights. In this blog post, we will explore real-world or real-life machine learning / deep learning / AI examples from daily life. We’ll see how machine-learning techniques have been successfully applied to solve real-life problems. The idea is to make you aware of how machine learning and data science applications are everywhere. What are some real-world examples of machine learning from daily life? Here are some real-world examples of machine learning that we use in our daily life: Best driving directions (Google Maps): A bunch of machine learning / deep …

The machine learning for accounts payable market is expected to grow from $6.1 million in 2016 to$76.8 million by 2021, at a compound annual growth rate (CAGR) of 53 percent. The software industry is rapidly embracing machine learning for account payable. As account payable becomes more automated, it also becomes more data-driven. Machine learning is enabling account payables stakeholders to leverage powerful new capabilities in this arena. In this blog post, you will learn machine learning / deep learning / AI use cases for account payable. Key Business Processes for Accounts Payable Here are the key business processes in relation to Accounts Payable: Supplier onboarding: Collect basic information about …