Tag Archives: Data Science
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 …
Hold-out Method for Training Machine Learning Models
The hold-out method for training the machine learning models is a technique that involves splitting the data into different sets: one set for training, and other sets for validating and testing. The hold out method is used to check how well a machine learning model will perform on the new data. In this post, you will learn about the hold out method used during the process of training machine learning model. Do check out my post on what is machine learning? concepts & examples for detailed understanding on different aspects related to basics of machine learning. When evaluating machine learning (ML) models, the question that arises is whether the model …
Hello World – Altair Python Install in Jupyter Notebook
This blog post will walk you through the steps needed to install Altair graphical libraries in Jupyter Notebook. For data scientists, Altair visualization library can prove to very useful. In this blog, we’ll look at how to download and install Altair, as well as some examples of using Altair capabilities for data visualization. What is Altair? Altair is a free statistical visualization library that can be used with python (2 or 3). It provides high-quality interactive graphics via an integrated plotting function ́plot() that produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms. Altair is also easy to learn, with intuitive commands like ‘plot’, ‘hist’ …
Most In-Demand Skills for Data Scientists in 2022
The data science field is growing rapidly and data scientists are in high demand. If you want to enter this field, it’s important that you have the right skills. In this blog post, we’ll explore the most in-demand skills of data scientist employers are looking for the most and how to develop these skills so that you can find a job as a data scientist. Strong experience with statistical/ML methods: Strong familiarity with probability distributions (e.g., normal distribution), concepts of hypothesis testing, regression analysis is essential for becoming a great data scientist. Data scientists are required to model data, assess the suitability of data for analysis, develop mathematical / machine …
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 …
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 …
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 …
Business Analytics Team Structure: Roles/ Responsibilities
Business analytics is a business function that has been around for years, but it’s only recently gained traction as one of the most important business functions. Organizations are now realizing how business analytics can help them increase revenue and improve business operations. But before you bring on a business analytics team, you need to determine if your company needs a full-time or part-time team member or both. It might seem logical to hire full-time analysts just because they’re in demand, but this isn’t always necessary. If your business operates without any external data sets and doesn’t have complex reporting needs then it may be more cost-effective to use freelancers rather …
Autoregressive (AR) models with Python examples
Autoregressive (AR) models are a subset of time series models, which can be used to predict future values based on previous observations. AR models use regression techniques and rely on autocorrelation in order to make accurate predictions. This blog post will provide Python code examples that demonstrate how you can implement an AR model for your own predictive analytics project. You will learn about the concepts of autoregressive (AR) models with the help of Python code examples. If you are starting on time-series forecasting, this would be useful read. Note that time-series forecasting is one of the important areas of data science / machine learning. Here are some of the topics that will be covered …
Neural Network Explained with Perceptron Example
Neural networks are an important part of machine learning, and so it is essential to understand how they work. A neural network is a computer system that has artificial neurons. It can be built to solve tasks, like classification and prediction problems. The perceptron algorithm is an example of how neural networks work. They were first proposed by Frank Rosenblatt in 1957 as models for the human brain’s perception mechanism. This post will explain the basics of neural networks with a perceptron example. You will understand about how a neural network is built using a perceptron. This is a very important concept in relation to getting a good understanding of …
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 …
What is Machine Learning? Concepts & Examples
Machine learning is a machine’s ability to learn from data. It has been around for decades, but machine learning is now being applied in nearly every industry and job function. In this blog post, we’ll cover what machine learning entails, how it differs from traditional programming. What is machine learning? Simply speaking, machine learning is a technology where in machine learns to perform a prediction/estimation task based on past experience represented by historical data set. There are three key aspects of machine learning which are following: Task: Task can be related to prediction problems Experience: Experience represents historical dataset Performance: The goal is to perform better in the prediction task …
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 …
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 …
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/ …
Difference between Data Science & Decision Science
Data science and decision science are two data-driven fields that have grown in prominence over the past few years. Data scientists use data to come up with conclusions or predictions about things like customer behavior, while decision scientists combine data with other information sources to make decisions. The difference between data science and decision science is important for business owners who want to make informed decisions. In this post, you will learn about the difference between data science and decision science. Those venturing out to learn data science must understand whether they want to learn data science or decision science or both. The following are some of the key questions …
