Author Archives: Ajitesh Kumar
Quick Notes on What is CAP Theorem?
This article briefly talks about what is CAP theorem and provides appropriate examples. I have come across many candidates appearing for architect interview who failed to answer the question such as some of the following: What is CAP theorem? RDBMS system such as Oracle achieves which of the following two: Consistency, Availability, Partition Tolerance NoSQL datastore such as HBase tends to achieve which of the following two: Consistency, Availability, Partition Tolerance The article below addresses some of the above questions. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following points are discussed later in this article: What is …
Data Science – Who could become a Data Scientist?
This article represents information related different classes of IT & Non-IT professionals who could take on different data science free courses (as mentioned) and get on to the path of becoming a data scientist. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the different classifications of IT/Non-IT professional which has been addressed later in this article: Software Development Stakeholders working on Non-analytics projects Datawarehouse/BI Developers Big Data Developers Statisticians Senior Management Executive Non-Software Professionals Could I become a Data Scientist? Anyone matching following criteria could become a data scientist. One is decent with Mathematics & Statistics …
Top 10 Solution Approaches for Supervised Learning Problems
This article represents top 10 solutions approaches that could be used to solve supervised learning problems. For those unaware of what is supervised learning problem, here is the supervised learning definition from Wikipedia: Supervised learning is the machine learning task of inferring a function from labeled training data.[1] The training data consist of a set of training examples. In supervised learning, each example is a pair consisting of an input object (typically a vector) and a desired output value (also called the supervisory signal). A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples. Following are two different kind of supervised …
Document Search Architecture to Search Millions of Documents
This article represents different document search architectural models using which one could create a search architecture that could search through 100s of millions of documents in faster time (milliseconds) with most up-to-date and fresh results. If you are planning to create a document search infrastructure which could search millions of documents, and shows up results in less than a second time, go ahead and explore different models and adopt the one that suits your needs at this stage. Note that the models given below could scale to multiple data centers. In this blog, we shall try and examine different architecture models that could achieve the search timing of less than a …
Top 10 Simpler Interview Questions, Architects Find Difficult to Answer
This article represents my list of top 10 interview questions which I see people, appearing for technical architect position, find difficult to answer. Although these questions seem to be simpler and subjective, I found candidates finding it difficult to answer. Do check the list below and see if you cracked all of them. Please feel free to comment/suggest if you would want me to include other questions. Sorry for the typos. Top 10 Interview Questions, Technical Architects Find Difficult to Answer Architecture & Design: Questions below are intended to test the candidates understanding on architectural frameworks and their abilities/capabilities to lay down system architecture/design. What are 3-4 most common …
Learn R or Python for Becoming Data Scientist?
This article presents analysis on whether one should go for learning R or Python programming language to create one or more predictive models using different machine learning algorithms. It could be noted that both languages, R and Python, is equally doing good and sought after by developers and the companies hiring such developers. So, you could choose either one of these languages. However, majority has been found to be voted in favour of Python for ease of learning and greater community support. Data Scientist with expertise in R Following indeed.com plot represents the job trends for the search term, “Data Scientist R”. It clearly indicates the trend such as …
Hello React Native! You Are So Cool!
This article represents a very high level introduction to React-Native platform and, highlights some of the key reasons as to why one would want to try and adopt this yet another mobile apps framework used for building native apps. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. React-Native is a framework for building native apps using ReactJS javascript framework. As of current release, it supports building iOS native apps using ReactJS framework. However, the primary objective has been to take the best of web and native platform and create a UIDeveloper-friendly framework that allows developers to write mobile …
Top 5 Interview Questions for Mobile Hybrid Apps Developer
This article represents top 5 most commonly asked interview questions for mobile hybrid apps developers. Please feel free to comment/suggest if you think of another most commonly asked interview questions in relation with hybrid apps development. Also, sorry for the typos. Top 5 Interview Questions for Mobile App Developers What are hybrid mobile apps? Ans: A detailed answer could be found here How are hybrid apps different from building native apps and mobile websites? Ans: Detailed answer could be found on this page. Why build native apps, when hybrid apps development frameworks are there? Ans: Some of the following could not be achieved effectively using web frameworks: Access to …
Machine Learning – Top 16 Learning Resources on Statistics
This article represents some of the top learning resources (webpages, videos etc) on my frequent visit list. 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 webpages/videos that are expanded later in this article: Websites Quora Youtube Videos Coursera courses Khan Academy Top 16 Learning Resources on Statistics Folllowing is the list of URLs for these learning resources: Websites on Statistics Stattrek.com Elementary Statistics with R StatsDirect.com Usable Stats Quora.com Statistics Channel Probability & Statistics Statistics (Acacedmic Discipline) Bayesian Inference Youtube Videos Playlists on Statistics Brandon Foltz StatisticsFun JBStatistics Quantitative Specialists Coursera Courses …
Machine Learning Research in Top 10 US Universities
This article represents information related with machine learning departments & related research projects in top 10 US universities (as per USNews Ranking). I have put it together for my quick reference and thought to share with you for the same purpose. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are top 10 universities covered later in this article: Princeton University Harvard University Yale University Columbia University Stanford University University of Chicago MIT Duke University University of Pennsylvania California Institue of Technology Machine Learning @ Top 10 US Universities Princeton University: Machine Learning Department at Princeton University …
Data Science – 175 Probability & Statistics Interview Questions
This article presents URL and short description of around 175 probability & statistics objective questions which could prove very useful and helpful for those who are planning to attend one or more data scientist interviews in time to come. These tests/quizzes were created when I was learning probability and statistics some time back and, found various concepts interesting enough to be converted into quizzes for my future references. As probability & statistics form key to data science, it may be worth spending some time on these tests and check your understanding. You may also use this for your future reference. These questions could also be used for checking your concepts …
Quick Cheat Sheet for Big Data Technologies
This article represents quick details on some of the key open-source technologies (tools & frameworks) associated with Big Data. The objective of this article is to present quick details on open-source tools & frameworks in a well-categorized manner using top-down approach where data engineering and data science aspects of Big Data is associated with relevant tools & framework. Most of these tools and frameworks could be found with commercial Hadoop distributions such as Cloudera, Hortonworks, MapR etc. Please feel free to comment/suggest if I missed to mention one or more important frameworks. Also, sorry for the typos. Following is the key classication of tools/frameworks that have been briefed later in …
Machine Learning – Top 5 Video Channels for Regression Models
This article represents top 5 video channels that one could use to learn and become expert at regression models. I make visits to watch these videos, once in a while, to clarify my doubts in relation with regression models. As I find these pages very useful, I thought it to share with you all. These are some real good videos from learning perspective that could help you get started with regression models and get a good hang of it within no time. Please feel free to share it with your community. Please feel free to comment/suggest if I missed to mention any other great video channels. Also, sorry for the …
Data Science – Top 10 Websites to Bookmark for Daily News
This article represents links and information in relation with top 10 websites that publishes data science related news and article on daily/regular basis. These links are my favorites and help me remain up-to-date with latest and greatest happening in the field of data science. Please feel free to comment/suggest if I missed to mention/include one or more important and interesting websites in the list given below. Also, sorry for the typos. Following are the key points described later in this article: Top 5 Data Science News Websites – Recommended Daily Visit Top 5 Data Science News Websites – Recommended Regular Visit Top 5 Data Science News Websites – Recommended …
Machine Learning – Mathematical Concepts for Linear Regression Models
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 …
Data Science – Descriptive Vs Predictive Vs Prescriptive Analytics
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 …
I found it very helpful. However the differences are not too understandable for me