Tag Archives: Data Science
10+ Key Stages of Data Science Project Life cycle
Data science projects need to go through different project lifecycle stages in order to become successful. In each of the stages, different stakeholders get involved as like in a traditional software development lifecycle. In this post, you will learn some of the key stages/milestones of data science project lifecycle. This article is aimed to help some of the following project stakeholders who play key roles in data science project implementation: Product managers Project managers ML architects The following represents 6 high-level stages of data science project lifecycle: Planning Model development & testing Product-level changes Model deployment Monitoring the model Model Enhancement Data Science Project Lifecycle – Planning ML Problem identification: …
Tutorials – Building Machine Learning Models for Predicting Cancer
In this article, I would introduce different aspects of the building machine learning models to predict whether a person is suffering from malignant or benign cancer while emphasizing on how machine learning can be used (predictive analysis) to predict cancer disease, say, Mesothelioma Cancer. The approach such as below can as well be applied to any other diseases including different types of cancers. Predicting Mesothelioma Cancer – Supervised Learning Problem Machine learning problems are classified into different kinds of learning problem. Most important of them are following: Supervised learning Unsupervised learning Supervised Learning In supervised learning, you have a history of data with each record being labeled. Thus, in case of predictive analysis of Mesothelioma cancer, there is …
Neural Networks Interview Questions – Set 2
This quiz represents practice test on artificial neural networks. These questions and answers can be as well used for your upcoming interviews for the position of machine learning engineer or data scientist. These questions can prove to be very useful for testing your neural networks knowledge from time-to-time. Also, these will be useful for interns / freshers / beginners of machine learning / data science. The topics covered in this practice test are following: Introduction to different types of neural networks such as Radial Basis Network, Recurrent neural network etc. Difference between multilayer perceptron (MLP) and Radial basis function network Practice Test on Neural Networks [wp_quiz id=”6000″]
70 Regression Analysis Interview Questions & Practice Tests
This page lists down practice tests (questions and answers), links to PDF files (consisting of interview questions) on Linear / Logistic Regression for machine learning / data scientist enthusiasts. These questions can prove to be useful, especially for machine learning / data science interns / freshers / beginners to check their knowledge from time-to-time or for upcoming interviews. Practice Tests on Linear / Multilinear Regression These are a set of four practice tests (consisting of 40 questions) covering linear (univariate) and multilinear (multivariate) regression in detail. Linear, Multiple regression interview questions and answers – Set 1 Linear, Multiple regression interview questions and answers – Set 2 Linear, Multiple regression interview …
Logistic Regression Interview Questions & Practice Tests
This page lists down a set of 30 interview questions on Logistic Regression (machine learning/data science) in form of objective questions and also provides links to a set of three practice tests that would help you test / check your knowledge on an ongoing basis. These questions and practice tests are intended to primarily help interns/freshers/beginners to help them brush up their knowledge in logistic regression from time to time. The following is a list of topics covered on this page. Introduction to logistic regression Logistic regression examples Evaluating performance of logistic regression and related techniques including AIC, deviance, ROC etc. Difference between linear and logistic regression Here is another post on …
Tutorials – Top 6 Linear Regression Tutorials for 2017
This page lists down top 6 machine learning tutorials (from Youtube) for the topic, Linear (Univariate) and Multilinear (Multivariate) regression from the perspective of most viewed / popularity. Following are the topics for these videos: How to Do Linear Regression using Gradient Descent Interpreting Output for Multiple Regression using SPSS R programming for beginners – statistic with R Linear Regression with Gradient Descent – Intelligence and Learning Linear Regression – Machine Learning Fun and Easy Linear Regression Algorithm | Linear Regression in R How to Do Linear Regression using Gradient Descent This tutorial video is posted on the channel Siraj Raval. They have got some real cool tutorial videos on …
Linear, Multiple Regression Interview Questions Set 4
This page lists down the practice tests / interview questions for Linear (Univariate / Simple Linear) / Multiple (Multilinear / Multivariate) regression in machine learning. Those wanting to test their machine learning knowledge in relation with linear/multi-linear regression would find the test useful enough. The goal for these practice tests is to help you check your knowledge in numeric regression machine learning models from time-to-time. More importantly, when you are preparing for interviews, these practice tests are intended to be handy enough. Those going for freshers / intern interviews in the area of machine learning would also find these practice tests / interview questions to be very helpful. This test primarily …
Linear, Multiple Regression Interview Questions Set 3
This page lists down the practice tests / interview questions for Linear (Univariate / Simple Linear) / Multiple (Multilinear / Multivariate) regression in machine learning. Those wanting to test their machine learning knowledge in relation with linear/multi-linear regression would find the test useful enough. The goal for these practice tests is to help you check your knowledge in numeric regression machine learning models from time-to-time. More importantly, when you are preparing for interviews, these practice tests are intended to be handy enough. Those going for freshers / intern interviews in the area of machine learning would also find these practice tests / interview questions to be very helpful. This test primarily …
Linear, Multiple Regression Interview Questions Set 2
This page lists down the practice tests / interview questions and answers for Linear (Univariate / Simple Linear) / Multiple (Multilinear / Multivariate) regression in machine learning. Those wanting to test their machine learning knowledge in relation with linear/multi-linear regression would find the test useful enough. The goal for these practice tests is to help you check your knowledge in numeric regression machine learning models from time-to-time. More importantly, when you are preparing for interviews, these practice tests are intended to be handy enough. Those going for freshers / intern interviews in the area of machine learning would also find these practice tests / interview questions to be very helpful. This …
Linear, Multiple Regression Interview Questions Set 1
This page lists down the practice tests / interview questions and answers for Linear (Univariate / Simple Linear) / Multiple (Multilinear / Multivariate) regression in machine learning. Those wanting to test their machine learning knowledge in relation with linear/multi-linear regression would find the test useful enough. The goal for these practice tests is to help you check your knowledge in numeric regression machine learning models from time-to-time. More importantly, when you are preparing for interviews, these practice tests are intended to be handy enough. Those going for freshers / intern interviews in the area of machine learning would also find these practice tests / interview questions to be very helpful. Note that …
Uber Machine Learning Interview Questions
This page represents some of the following in relation with Uber Data Science / Machine Learning interview questions: Interview questions Data Science challenge Machine learning problems These questions / problems etc have been gathered from different websites and blogs including Glassdoor, Github, Blogs etc. Data Science / Machine Learning Interview Questions Uber’s surge pricing algorithm including optimization techniques which can be used. Here is a great write up on The secrets of Uber’s mysterious surge pricing algorithm, revealed How would you find / investigate an anomaly in a distribution? What are different Time Series forecasting techniques? Explain Principle Component Analysis (PCA) with equations? How would you go about solving Multicollinearity? …
Introduction to Machine Learning (Set 2) Interview Questions
This page represents a list of questions which can be used for preparation of machine learning interviews. Here is the link to first set of machine learning interview questions as part of this series. The following are some of the areas covered in this set of questions: Univariate vs Multivariate linear regression Supervised vs unsupervised learning Algorithms such as KNN, K-means, SVM etc. [wp_quiz id=”5748″]
Machine Learning (Ensemble Techniques) Interview Questions
This page represents a list of questions which can be used for preparation of machine learning interviews. The following are some of the topics covered in this set of questions: Ensemble learning: Ensemble learning algorithms are used to improve the prediction performance of individual learning algorithms based on bagging or boosting technique. Bagging (Boosting Aggregation) Boosting Decision trees Random forest [wp_quiz id=”5764″]
18 Microsoft Data Science Interview Questions
This is a list of 18 questions which has been asked in several Microsoft data science / machine learning interviews. These questions have been compiled from Glassdoor and other sources. We shall be posting a series of related objective questions (capsule) quizzes in very near future. Can you explain the Naive Bayes fundamentals? How did you set the threshold? Can you explain SVM? How do you detect if a new observation is outlier? What is bias-variance trade off ? Basic statistical questions such as define variance, standard deviation etc Discuss how to randomly select a sample from a product user population. Describe how gradient boost works. What is L1 and …
Machine Learning (Hypothesis Testing) Interview Questions
This page represents a list of questions which can be used for preparation of machine learning interviews. The following are some of the areas covered in this set of questions: Null Hypothesis; Another page which explains the concept in decent manner is Null Hypothesis definition and examples, how to state. P-value; In simple words, p-value represents likelihood (in terms of probability) of sample results occurring if the null hypothesis is assumed to be true. For example, a p-value of 0.03 would mean that given the null hypothesis is true, the probability that results occur in the sample is 0.03 which is very less. Thus, the alternate hypothesis can be true. Thus, …
Amazon Machine Learning Interview Questions Set 2
This page lists down second set of objective questions which represents interview questions that have been asked in various amazon machine learning interviews. Here is the first set of questions. These questions have been gathered from sources such as Glassdoor and other places on the internet. Following areas are covered in this set of questions: Generative and discriminative algorithms Gradient descent vs stochastic gradient descent (SGD) Cost functions [wp_quiz id=”5741″]
I found it very helpful. However the differences are not too understandable for me