Tag Archives: machine learning

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 , , , .

Hold-out Method for Training Machine Learning Models

Hold-out-method-Training-Validation-Test-Dataset

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 …

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Posted in Data Science, Machine Learning. 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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Deep Neural Network Examples from Real-life

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

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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Difference between Supervised & Unsupervised Learning

Supervised vs Unsupervised Machine Learning Problems

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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Business Analytics Team Structure: Roles/ Responsibilities

business analytics team structure roles and 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 …

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Google Cloud Automl: Business Application Examples

Google cloud platform GCP Automl Services

Google cloud platform (GCP) automl services are a set of google cloud platform products with a focus on machine learning and automation. They help you to automate several tasks related to machine learning. In this blog post, we’ll talk about google cloud automl services and some common business problems that can be solved using these GCP automl services. What are some popular Google Cloud Automl services? Google cloud automl services include some of the following: Google Cloud Vision can be used to perform tasks related to image recognition like face detection, OCR (optical character recognition), landmark detection, etc. Google’s cloud vision can detect emotions, understand text, and more. The service …

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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 …

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

Neural Network Explained with Perceptron Example

Single layer neural network

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 …

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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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What is Machine Learning? Concepts & Examples

what is machine learning

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 …

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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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Different Types of CNN Architectures Explained: Examples

VGG16 CNN Architecture

The CNN architectures are the most popular deep learning framework. CNNs are used for a variety of applications, ranging from computer vision to natural language processing. In this blog post, we will discuss each type of CNN architecture in detail and provide examples of how these models work. Different types of CNN Architectures The following is a list of different types of CNN architectures: LeNet: LeNet is the first CNN architecture. It was developed in 1998 by Yann LeCun, Corinna Cortes, and Christopher Burges for handwritten digit recognition problems. The model has five convolution layers followed by two fully connected layers. LeNet was the beginning of CNNs in deep learning …

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Real-World Applications of Convolutional Neural Networks

Input image along with convolutional layer

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

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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