Tag Archives: big data

Data Science – Hypothesis Testing Explained with Examples

Hypothesis Testing Workflow

This article represents some of the key statistical concepts along with examples in relation with how to formulate a hypothesis for hypothesis testing. The knowledge of hypothesis formulation and hypothesis testing would prove key to building various different machine learning models. In later articles, hypothesis formulation for machine learning algorithms such as linear regression, logistic regression models etc., will be explained. Please feel free to comment/suggest if I missed mentioning one or more important points. Also, sorry for the typos. Following are the key points described later in this article: What is a hypothesis? How to formulate a hypothesis as Null or Alternate Hypothesis? What is hypothesis testing? What is a …

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

Machine Learning – Mathematical Concepts for Linear Regression Models

linear regression model

This article represents some of the key mathematics & statistics concepts that one may need to learn in order to work with linear regression models. Understanding following concepts would help in some of the following manners in relation with evaluating linear regression models: Interpreting coefficients Evaluating the regression model Comparing multiple regression models and choosing the best out of them 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 mathematical concepts/topics described later in this article: Statistical hypothesis testing Probability distributions Quantitative data analysis Plots   Key Mathematics & Statistics Topics for Linear Regression Models …

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Data Science – Descriptive Vs Predictive Vs Prescriptive Analytics

Descriptive vs Predictive vs Prescriptive

This article represents key classification or types of analytics that business stakeholders, in this Big Data age, would want to adopt in order to take the most informed and smarter decisions for better business outcomes. 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 categories of analytics which are described later in this article: Descriptive Analytics Predictive Analytics Prescriptive Analytics What is Descriptive Analytics? Descriptive analytics answers the question or gains insights into or summarize, “What has happened?”. This could be seen as first stage of business analytics and still accounts for the majority of …

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Data Science – Key Algebra Topics to Master

algebra topics for data science

This article represents some of the key topics in Algebra that one may need to brush up or master in order to get good at understanding different aspects of machine learning algorithms. If you are gearing up to become the data scientist, the topics below may be worth your attention as I had to brush them up eventually when I was learning different machine learning algorithms. The concepts listed below, especially related with linear algebra, touches almost all machine learning algorithms. 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 high level topics which are …

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Data Science – Key Probability & Statistics Topics to Master

Table of content for probability & statistics

This article represents a list of key probability & statistics topics that one may need to master if he is aiming to become a data scientist. This article lists topics that has worked for me so far in relation with working on a data science problem. One could also see the below list as table of content for key probability and statistics topics for data science. However, I do believe that there are some topics that I might not have mentioned. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Probability & Statistics Topics Following are some of the …

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Machine Learning – Bookmarks for Great Tutorials, Books & Videos

This article represents quick bookmarks on some good machine learning web pages including tutorials’ documents and videos. Please feel free to comment/suggest if you know of further good bookmarks. I shall be adding more bookmarks in time to come. Also, sorry for the typos. Following are the key bookmarks: List of Tutorial Pages on Different Machine Learning Topics: You shall surely want to bookmark this page as it consists of some real cool links covering different topics in machine learning. List of Machine Learning Books: Those looking out for machine learning books to get started would want to bookmark this page which consists of list of some great books recommended …

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Machine Learning – When to Use Logistic Regression vs. SVM

Logistic Regression vs SVM

This article represents guidelines based on which one could determine whether to use Logistic regression or SVM with Kernels when working on a classification problem. These are guidelines which I gathered from one of the Andrew NG videos on SVM from his machine learning course in Coursera.org. As I wanted a place to reach out quickly in future when I am working on classification problem and, want to refer which algorithm to use out of Logistic regression or SVM, I decided to blog it here. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Key Criteria for Using Logistic Regression vs …

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Machine Learning – When to Use Linear vs Guassian Kernel with SVM

This article represents guidelines which could be used to decide whether to use Linear kernel or Gaussian kernel when working with Support Vector Machine (SVM). 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: When to Use Linear Kernel When to Use Gaussian Kernel   When to Use Linear Kernel In case there are large number of features and comparatively smaller number of training examples, one would want to use linear kernel. As a matter of fact, it can also be called as SVM with No Kernel. One may …

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8 Key Steps to Follow When Solving A Machine Learning Problem

This article represents some of the key steps one could take in order to create most effective model to solve a given machine learning problem, using different machine learning algorithms. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. 8 Key Steps for Solving A Machine Learning Problem Gather the data set: This is one of the most important step where the objective is to as much large volume of data set as possible. Given that features have been selected appropriately, large data set helps to minimize the training data set error and also, enable cross-validation and training data set error …

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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 …

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Big Data – Top Education Resources from MIT

MIT CSAIL Big Data

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 …

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API – How to Get Started with Facebook API Integration

This article represents steps to get started with Facebook Graph API. In later articles, I shall explain how to integrate using Java and maybe other programming languages. The primary reason I am hooked to Facebook integration these days is my need for getting exploratory data from facebook for data analysis for my Big Data projects. Before getting onto use framework such as RestFB, it is recommended to play with these APIs in the Facebook-provided playground.  I shall be talking in detail about how to get started with RestFB in later articles. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the …

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Data Science – Quick Start Guide for Machine Learning

machine learning

This article represents a very high-level information on different aspects of machine learning with an objective to present a quick-start read/guide for the data science beginners. One could grab one or more books on Machine Learning to learn the subject in detail. 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: What is machine learning? Key phases of machine learning Prediction API model of machine learning   What is Machine Learning? Simply speaking, Machine Learning is a set of artifical intelligence techniques which are used to solve one of …

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Data Scraping – Top 5 Reasons for using Import.io Tool

This article represents my thoughts on why one would want to use this web data scraping tool, named as import.io. I must say that I am glad I found this tool for data scraping. 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: Key aspects of Import.io Reasons Why One Must Try Import.io for their next Data Scraping Project Use-cases where Import.io scraping tool could be used   Key Aspects of Import.io Tool Import.io is a cloud-based web scraping tool which could act as a boon for those looking …

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Data Science – 8 Steps to Perform Regression Analysis using R

This article represents my thoughts on steps that may be required to perform regression analysis (linear or multiple) using R programming language, on a given data set where response variable is primarily a continuous variable. Remember that continuous variables are the ones which could take any numeric data unlike discreet variables which could take only limited set of data. 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 steps described later in this article: Load the data Observe the data Clean the data Explore the data visually Fit the linear or multiple regression model …

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Learn R – Hello World with R – Code Example

This article represents some of the basic concepts required to be understood to write Hello world using R programming language and, execute the same. 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: Basic Concepts to Write Hello World Function in R Hello World – Code Example Basic Concepts to Write Hello World Function in R Following are some key points to pay attention at, while working Hello World example: R code is written as a set of one or more functions. In R, one could assign a function …

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