Tag Archives: machine learning
Machine Learning – How to Diagnose Underfitting/Overfitting of Learning Algorithm
This article represents technique that could be used to identify whether the Learning Algorithm is suffering from high bias (under-fitting) or high variance (over-fitting) problem. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key problems related with learning algorithm that are described later in this article: Under-fitting Problem Over-fitting Problem Diagnose Under-fitting & Over-fitting Problem of Learning Algorithm The challenge is to identify whether the learning algorithm is having one of the following: High bias or under-fitting: At times, our model is represented using polynomial equation of relatively lower degree, although a higher degree of …
Machine Learning – 7 Steps to Train a Neural Network
This article represents some of the key steps required to train a neural network. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Key Steps for Training a Neural Network Following are 7 key steps for training a neural network. Pick a neural network architecture. This implies that you shall be pondering primarily upon the connectivity patterns of the neural network including some of the following aspects: Number of input nodes: The way to identify number of input nodes is identify the number of features. Number of hidden layers: The default is to use the single or one hidden …
Data Science – 8 Steps to Multiple Regression Analysis
This article represents a list of steps and related details that one would want to follow when doing multiple regression analysis. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key points described later in this article: 8 Steps to Multiple Regression Analysis Techniques used in Multiple regression analysis 8 Steps to Multiple Regression Analysis Following is a list of 7 steps that could be used to perform multiple regression analysis Identify a list of potential variables/features; Both independent (predictor) and dependent (response) Gather data on the variables Check the relationship between each predictor variable …
Big Data – Top Education Resources from MIT
This article represents information on Big Data initiative from MIT (Massachusetts Institute of Technology) including bookmarks on lecture notes related machine learning courses and also, machine learning video channel from MIT on Youtube. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key points described later in this article: MIT CSAIL Big Data Initiative Machine Learning Lecture Notes & Videos MIT CSAIL Big Data Initiative MIT has a website dedicated to Big Data initiative from MIT CSAIL (Computer Science and Artificial Intelligence Laboratory). Following pages are worth visits to understand ongoing research and listen/view talks …
Weekly Roundup – Machine Learning & Statistics Bookmarks – 02 Feb 2015
This article represents links to some of cool pages on machine learning & statistics that I thought worth sharing. Please feel free to comment/suggest any other webpages that found to be good. Sorry for the typos. Machine Learning & Statistics Bookmarks Andrew NG: One starting to learn machine learning is sure to come across course, paper, or a web page related with Andrew NG, an Associate Professor at Stanford; Chief Scientist of Baidu; and Chairman and Co-Founder of Coursera. Some of the pages sighting his work are following: Courses Publications Research Andrew W. Moore: Great set of tutorials by Andrew D. More, who is Dean of the School of Computer …
Machine Learning – 9 Most Common Usecases for Higher Business Growth
This article represents some of the most common use cases of machine learning algorithms which has been found to impact business growth (in terms of revenues) in a positive manner. These usecases could be most commonly seen with all businesses which are running some or the other form of ecommerce site to support one or more aspects of their business. I have tried and provide information regarding which algorithm (or class of algorithm) could be used to come up with a solution for these usecases. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are different areas, at …
Top 4 Machine Learning Usecases for Energy Forecasting
This article represents top 4 machine learning usecases for energy forecasting. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Machine Learning Usecases for Energy Forecasting Following are different usecases in relation with energy management where machine learning could be used for probabilistic energy forecasting. For those who are new to probabilistic forecasting, here is the definition from Wikipedia: Probabilistic forecasting summarises what is known, or opinions about, future events. In contrast to a single-valued forecasts (such as forecasting that the maximum temperature at given site on a given day will be 23 degrees Celsius or that the result …
Machine Learning Usecases for Pinterest.com & related Kosei Acquisition
This article represents thoughts on recent acquisition of Kosei, a commerce recommendation system, by Pinterest.com. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key points described later in this article: How could Machine Learning help Pinterest fuel its overall growth? How could Kosei help Pinterest.com? How could Machine Learning help Pinterest fuel its overall growth? Yet another acquisiton in the space of machine learning, Pinterest.com acquires Kosei to achieve some of the following objective: Better ad targeting for greater mometization from ad clicks. This looks to be a case of identifying users clusters based …
I found it very helpful. However the differences are not too understandable for me