How should I prepare for statistics questions for a data science interview? What topics should I brush up on?
Thanks for A2A.Actually bunch of people have written good answers and i personally liked that of Jeffrey Wong and Nigel Clay.Just to add my two cents, when it comes to selecting right candidates, i personally give emphasis on mainly two things: the conceptual understanding than mere theory, and passion to learn new things. i have seen enough people in my life who are just too good at theory but when it comes to practical implementation, they can not apply that knowledge to solve the business problem.And by chance if you stumbled upon such person in the interview who is looking for specific answer only and doesn't care about the systematic approach, i would say that company (or at least that person's job) is not for you! There are few opportunities in life which you have to let go so that some much better opportunity is waiting for you in the future! Its not just philosophy but i have (and am) experienced (and experiencing) it!I am sure the original questioner's interview must be over long back but still all the best for future interviews of all the readers! :)
How can I evaluate Pesq-MOS results?
MOS value subjective to call quality of call. MOS value score range from 1 UN-acceptable to 5 -acceptable. VOIP calls are in the range of 3.5 to 4.2.
Which is the best training center for machine learning with R/Python/SAS in Chennai?
Hi Dear friends,Currently, Machine learning technology is one of the booming technology in IT industry. There are many institutes offering Machine course with class room training as well as online training. You have many choice to choose which training center is best place to learn machine learning course. I strongly suggest SLA is reputed training institute provides Machine learning training in Chennai.SLA not only offer Machine Learning, they offer all the technologies which is related to data science such as R training, Python Training, SAS Training.If anyone have a dream to start career in Machine learning with Data Science, SLA is the right choice for you start your career as a Data Scientist.For more Details Contact SLA at +91 86087 00340.Visit: Machine Learning Training in Chennai | Best Machine Learning Training Institute in ChennaiCourse Content:Machine Learning Using R SyllabusModule 1- Introduction to Data AnalyticsModule 2- Introduction to R programmingModule 3- Data Manipulation in RModule 4- Data Import techniques in RModule 5 – Loops and DateModule 6 – Exploratory Data AnalysisModule 6- Statistics and Machine Learning – Regression and ClassificationModule 7- Project work
What is the difference between i3 and i5 processor?
i3 Processor simply means that you have 2 processor that can perform hyperthreading task individually (i.e=> in common terms each processor can do two task almost simultaneously) so i3 processor behaves as if it have 4 processors embedde in it On the other hand i5 processor really contains 4 processors each capable of doing single task at a time but very efficiently. And pf course i5 processor will be more efficient as it have 4 dedicated core for each task to do. Talking about frequency 2.4GHz simply means that the processor as a whole can process or binary task (2.4 * 10 raised to 12 power) in one second & 1.8GHz similarly means that it can perform 1.8*10 raised to 12 power) processes in one second. So for the same processor configurartion higher frequency processor will do work fficiently. But here by combing both the effects it will be decided which will perform task better & cant be predicted mathematically or logically.
What is the best pickup line for programmers?
I believe Programmer Ryan Gosling says it best.And if he hasn't stolen your girl's const pointer yethe will have now.Can't say no to that.And my personal favorite:----[Edit:] So this answer has been taken down several times because it violates Quora's no meme policy. I keep trying to put it back up because people have actually messaged me that they really liked my answer and want to see it uncollapsed (thanks by the way, it made me happy). I'd like to argue that while this answer does include meme pictures, it is in fact very helpful to someone interested in learning the answer to the question, and that is what Quora should be placing a priority on. What's wrong with presenting relevant information in a humorous way anyways? And is this enough text to keep it from being filtered?[Edit:] Thanks for the tip, Konstantinos.Hey girl, you have a const pointer to my heart.Hey girl, you are the stop condition to my heart's search algorithm.Hey girl, when you traverse my tree, I'll let you visit every node.Hey girl, fork my heart because I'm ready to commit.Hey girl, did you lose a timestamp? Because I'm pretty sure it's DateTime.Now() Courtesy of http://programmerryangosling.tum....
How do I start a career in Machine learning? Which language should I choose? What are the topics to cover as an absolute beginner?
Interested in the field of Machine Learning? Then this Udemy course is for you!Course link- Machine Learning A-Z™: Hands-On Python & R In Data Science-Learn to create Machine Learning AlgorithmsLearn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.This course has been designed by two professional Data Scientists so that we can share their knowledge and help you learn complex theory, algorithms and coding libraries in a simple way.They will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.This course is fun and exciting, but at the same time they dive deep into Machine Learning. It is structured the following way:Part 1 - Data PreprocessingPart 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest RegressionPart 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest ClassificationPart 4 - Clustering: K-Means, Hierarchical ClusteringPart 5 - Association Rule Learning: Apriori, EclatPart 6 - Reinforcement Learning: Upper Confidence Bound, Thompson SamplingPart 7 - Natural Language Processing: Bag-of-words model and algorithms for NLPPart 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural NetworksPart 9 - Dimensionality Reduction: PCA, LDA, Kernel PCAPart 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoostFor Artificial Intelligence learn from this course-Course Link- Artificial Intelligence A-Z™: Learn How To Build An AI
What's the difference between aov() and anova() in R? How are they used?
aov() performs 1 way ANOVA. The generic anova() is used to compute the analysis of variance (or deviance) tables for one or more fitted model objects (Type I). The anova() in the car package may be used to get the two way ANOVA table.To run an ANOVA using aov() run the function, store the output and use extraction functions to use what you need, e.g.: >aov.out = aov(count ~ spray, data=InsectSprays) >summary(aov.out)To produce an Analysis of Variance table for a model:>anova(plant.mod1) Analysis of Variance TableResponse: weight Df Sum Sq Mean Sq F value Pr(>F) group 2 3.7663 1.8832 4.8461 0.01591 * Residuals 27 10.4921 0.3886--- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1