InTDS ArchivebyKessie ZhangHow to Prepare for Business Case Interview as an Analyst?As a data analyst or data scientist, we not only need to know probabilities and statistics, Machine learning Algorithm, most importantly…Aug 28, 2020Aug 28, 2020
InLunarTechbyTatev Karen AslanyanFundamentals Of Statistics For Data Scientists and Data AnalystsKey statistical concepts for your data science or data analytics journeyApr 17, 202110Apr 17, 202110
Adnan UmarHow to Measure the Success of Your Marketing CampaignsWhen it comes to marketing, you’ve got to know if what you’re doing is working.May 26, 20231May 26, 20231
InThe Alpha StrategistbyAbhinav ChouhanAn Insider’s Guide to Predictive Modeling ComparisonAug 11, 2014Aug 11, 2014
InTDS ArchivebyRaimi Karim10 Gradient Descent Optimisation AlgorithmsStochastic gradient descent optimisation algorithms you should know for deep learningNov 22, 20183Nov 22, 20183
InTDS ArchivebyMd Sohel MahmoodLogistic Regression: Statistics for Goodness-of-FitStatistics in R Series: Deviance, Log-likelihood Ratio, Pseudo R² and AIC/BICOct 17, 2022Oct 17, 2022
InTDS ArchivebyPracticus AIThe 5 Clustering Algorithms Data Scientists Need to KnowFeb 5, 201855Feb 5, 201855
InData Science in your pocketbyMehul GuptaVarious Data Distributions in StatisticsAs promised in my last article(20+ stats concepts for Data Science), this time I would be exploring different data distributions a Data…Jul 25, 20191Jul 25, 20191
InAnalytics VidhyabyYash ChoksiModel selection: Cp, AIC, BIC and adjusted R2Significance and meaning of Cp, AIC, BIC and adjusted R²Mar 6, 20202Mar 6, 20202
InHeartbeatbyPrince Grover5 Regression Loss Functions All Machine Learners Should KnowChoosing the right loss function for fitting a modelJun 5, 201827Jun 5, 201827
InTDS ArchivebyMaheshEverything You Need To Know about Hypothesis Testing — Part IStatistics is all about data but data alone is not interesting. It is the Interpretation of the data that we are interested in…Sep 10, 20199Sep 10, 20199
InGeek CulturebyAbhishek MungoliA Complete Guide to Linear RegressionCovering all the fundamentals of Linear RegressionOct 8, 2021Oct 8, 2021
InDeep Learning DemystifiedbyHarsha BommanaUnderstanding OptimizersExploring how the different popular optimizers in Deep Learning workOct 7, 20193Oct 7, 20193
InTDS ArchivebyJoseph RoccaEnsemble methods: bagging, boosting and stackingUnderstanding the key concepts of ensemble learning.Apr 23, 201937Apr 23, 201937
InTDS ArchivebySamuele Mazzanti6 Types of “Feature Importance” Any Data Scientist Should KnowA complete guide to “feature importance”, one of the most useful (and yet slippery) concepts in MLDec 28, 20217Dec 28, 20217
InTDS ArchivebyAmanda Iglesias MorenoMoving averages with PythonSimple, cumulative, and exponential moving averages with PandasJul 8, 20205Jul 8, 20205
InTDS ArchivebyEligijus BujokasFeature Importance in Decision TreesA complete Python implementation and explanation of the calculations behind measuring feature importance in tree-based algorithmsJun 2, 20221Jun 2, 20221
InGoPenAIbyJoanna8 Anomaly Detection Techniques: Summary, Comparison, and Code“An outlier is an observation which deviates so much from the other observations as to arouse suspicions that it was generated by a…Aug 26, 2022Aug 26, 2022
InTDS ArchivebySamuele MazzantiYour Dataset Is Imbalanced? Do Nothing!Class imbalance is not a problem. Debunking one of the most widespread misconceptions in the ML community.Aug 24, 202229Aug 24, 202229
