Machinelearning made easy

#15 Boosting Algorithms
Let's take you through the advantages and disadvantages of Xgboost













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#14 Boosting Algorithms
Let's learn about Post Prunning😃












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#5 End-to-end Implementation of MLOps😀
QnA - Brainstorming
Let's windUp with some QansAs and Feedback

#13 Boosting Algorithms
Let's Understand the working of Xgboost 😎













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#4 End-to-end Implementation of MLOps😀
This tutorial depicts a sample use case of a simple ML using the IRIS Dataset to classify the IRIS flower (its species) and we have used DecisionTreeClassifier for the same. The tutorial shows an end-to-end CI/CD pipeline deployment on MS Azure using a few CLI commands (source available on Github: https://github.com/sagnik0712mukherjee/AZURE-MLOps-IRIS).

#12 Boosting Algorithms
Coming to Another Interesting topic - Xtreme Gradient Boosting



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#3 End-to-end implementation of MLOps 😀
Theoretical understanding of CI/CD
Definition of the CI/CD pipeline specifications with an explanation of the block diagram which shows each step involved in the process(es)





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#11 Boosting Algorithms
How is Ada Boosting different from Gradient boosting🤔
Let's understand here!














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#2 End-to-end Implementation of MlOps
Here, The various Principles of MLOps have been described in detail which also include an introduction to important terms like CI, CD, CT, and CM.

#10 Boosting Algorithms
This clip explains the practical application of Gradient Boosting













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