Category Archives: Data Science

P-Value & Hypothesis Testing: Examples

P-value explained with examples

Many describe p-value as the probability that the null hypothesis holds good. That is an incorrect definition. The concept of p-value is understood differently by different people and is considered as one of the most used & abused concepts in statistics, mostly in relation to hypothesis testing. In this blog post, you will learn the P-VALUE concepts with multiple different examples. It is extremely important to get a good understanding of P-value if you are starting to learn data science/machine learning as the concepts of P-value are key to hypothesis testing. Before getting into the description of p-value, let’s quickly go through the hypothesis testing concepts to get a good …

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Posted in Data Science, statistics. Tagged with , .

Type I & Type II Errors in Hypothesis Testing: Examples

This article describes Type I and Type II errors made due to incorrect evaluation of the outcome of hypothesis testing, based on a couple of examples such as the person comitting a crime, the house on fire, and Covid-19. You may want to note that it is key to understand type I and type II errors as these concepts will show up when we are evaluating a hypothesis such as those related to machine learning algorithms (linear regression, logistic regression, etc). For example, in the case of linear regression models, the significance value is compared with the p-value and, the null hypothesis that the parameter/coefficient is equal to zero is …

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Python – Matplotlib Pyplot Plot Example

matplotlib pyplot plot example artistic layer

Matplotlib is a matlab-like plotting library for python. It can create both 2D and 3D plots, with the help of matplotlib pyplot. Matplotlib can be used in interactive environments such as IPython notebook, Matlab, octave, qt-console and wxpython terminal. Matplotlib has a modular architecture with each layer having its own dependencies which makes matplotlib very versatile and allows users to use only those modules they need for their applications. matplotlib provides many hooks that allow developers to customize matplotlib features as they need. Matplotlib architecture has a clear separation between user interface and drawing code which makes it easy to customize or create new interfaces for matplotlib. In this blog …

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Survival Analysis Modeling for Customer Churn

survival analysis customer churn

Customer churn is a prevalent problem for many businesses. It can happen in several different ways, such as when customers stop using the product, or when they leave because of an issue with customer service. This blog post will explore survival analysis modeling and what it can do to help you better understand customer churn problems. First, we will discuss survival analysis itself and why it is beneficial for analyzing customer behavior. Then we will show some examples on how survival analysis has been used to analyze customer churn problems. As data scientists, it will be good to familiarize ourselves with survival analysis, as it is a popular modeling technique …

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Posted in Data Science, statistics. Tagged with , , .

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

Hello World – Altair Python Install in Jupyter Notebook

Altair visualization python

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’ …

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Posted in Data Science, Python. Tagged with , .

Different types of Machine Learning: Models / Algorithms

supervised vs unsupervised machine learning

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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Free AI / Machine Learning Courses at Alison.com

free machine learning courses at alison

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

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

NIT Warangal one week course on AI and 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

ML Engineer vs Data Scientist

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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Week Nov1, 2021: Top 3 Machine Learning Tutorial Videos

machine learning deep learning data science courses Nov 1 2021

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

neural networks 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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Machine Learning Examples from Daily Life

machine learning models development and deployment challenges

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 …

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8 Months Data Science Program from IIT Chennai

data science course from IIT madras

Are you looking for a new job or build your career in the field of data science? Data science is the hottest career in India right now. It is one of the most sought after skills today. It’s not just about crunching numbers anymore – it’s an exciting, dynamic field that requires creativity and critical thinking. With data science, you can solve problems and make a real impact on society. And with IIT Madras offering diplomas in data science, there has never been a better time to get started! IIT Madras has launched its diploma program in Data Science for college students, working professionals and job seekers who aim to …

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Stock Price Prediction using Machine Learning Techniques

Stock movement machine learning techniques

In the past few decades, many advances have been made in the field of data analytics. Researchers are now able to predict stock prices with higher accuracy due to analytical predictive models. These predictive techniques utilize data from previous stock price movements and look for patterns that could indicate future stock price changes in the market. The use of these machine learning techniques will allow investors to make better decisions and invest more wisely by maximizing their returns and minimizing their losses. In this blog post, you will learn about some of the popular machine learning techniques in relation to making stock price movement (direction of stock price) predictions and …

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Data Readiness Levels Assessment: Concepts

data readiness levels assessment

Data readiness levels (DRLs) and related assessments are an important part of data analytics. Data readiness levels is a concept where different stages represent the quality and maturity of data. Data science is becoming increasingly popular, but not all companies have the right level of data readiness for this type of work. Performing data readiness levels assessment is important because it gives an insight into the quality and quantity of your current datasets and helps determine future success of the data analytics project. This blog post will explain what data readiness levels are and why assessment tests are important in relation to them. What are data readiness levels? Data readiness …

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