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Data Science, Machine Learning & Artificial Intelligence

by Ashutosh Tripathi

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EXPORT TO EXCEL USING OPEN XML IN MVC

July 6, 2017 Ashutosh Tripathi

In Your View

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Precedence Graph to check Conflict Serializable Schedule

April 15, 2017 Ashutosh Tripathi

Precedence graph algorithm can be used to find out whether the given concurrent schedule is conflict serializable or not. Algorithm: Create the number of node

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ASP .NET MVC Architecture History

March 9, 2017 Ashutosh Tripathi

MVC 6.0 | ASP .NET vNext Single Programming Model for ASP.NET MVC and ASP.NET Web API. Cloud

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If you are an aspiring data scientist or an experienced professional who is trying to make his career in Data Science, then this platform is for you. In Mock Interviews, we focus on high-quality interactive interview sessions. You have the option to schedule two kinds of Mock Interviews with us. Generic (AI, ML or DS) Interview to prepare on all the topics. Company-specific Job Description based Interview. If you like the platform please contact us using https://enetwork.ai/contact-us Thank you. #artificialintelligence #enetwork-ai #ashutosh_ai #machinelearning #trending #interview #coaching #interviewadvice #mockinterview #datascienceingerview #technology #hire #mentor #mentorship

#Boosting is the technique which helps to improve the accuracy of the #machinelearning models. We apply boosting when none of the available models gives the good accuracy. One major difference between bagging and boosting is that bagging is used mainly to reduce the model variance and as a result also improve the accuracy upto some extent. However, boosting is used to improve accuracy not to reduce model variance. In boosting we train same model many times by assigning different wights to the misclassified observations in previous training. Hence by repeating this step multiple times tend to classify most observations correctly. In bagging we take different sample with replacement all together to train the model in next iteration. However model family remains the same in each iteration in both bagging as well as in boosting. #artificialintelligence #machinelearning #ai #technology #datascience #bigdata #deeplearning #tech #innovation #python #iot #blockchain #robotics #programming #coding #business #developer #digital #robots #startup #engineering #data #automation #analytics #robot #ml #cloudcomputing #digitaltransformation #ashutosh_ai

Guys, if you are someone who is interested in #AI #ML and #datascience , here is the list of 20 influencers whom you must follow. Thank you Arjun K. For compiling the list and I am so grateful that you included me. I will try my best to keep on writing the useful content. If you want to connect with them in linkedin, the link is in the description. #artificialintelligence #machinelearning #technology #ashutosh_ai #robotics #iot

Guys, please find the quick refresher on #Overfitting in #ml #model Share your thoughts on overfiting and which method you used to overcome it. #ashitosh_ai #artificialintelligence #machinelearning #imarticus #learning #share #shareyourstory #infographics #latest #friday #morning #goodmorning #dailythoughts #iot #trendingnow @imarticus @insofe_global @artificial_intelligence_ml

Many colleagues have asked me the same question. How to start #career in #datascience and #machinelearning . So thought of writing an article on this topic based on my past experience. The complete article is available in the below link: https://ashutoshtripathi.com/2019/11/17/how-to-start-career-in-data-science-and-machine-learning/ What are your thoughts on the same. Share them using comment, also if you want to include same in the article let me know. #ashutosh_ai #artificialintelligence #careerinai #latest #technology #knowledgesharing #Infographics #goodevening #weekend #data #analytics #ml #ai

Variance and Standard deviations are the most used measures of central tendencies in #datascience and #Statistics . Also it is important to understand what difference it brings when we already have #mean nad #median . In other words we can say when mean is not enough to decide the central tendencies. #artificialintelligence #machinelearning #ai #technology #bigdata #deeplearning #tech #innovation #python #iot #blockchain #robotics #programming #coding #business #developer #digital #robots #startup #engineering #data #automation #analytics #robot #ml #ashutosh_ai

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