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Saurabh Jain

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Blog Entries posted by Saurabh Jain

  18. Saurabh Jain
    In this case, we will analyze sales data from two stores and answer the following questions
    What percentage of sales occur at each store ? What percentage of sales occur at each month ? How much revenue does each product generated? Which products generate 80 % of revenue? We will also learn the Use of Report Filters & Slicers
     
     
    Download data set
     
  21. Saurabh Jain
    In this tutorial we will learn to write basic formulas and introduction to cell referencing
    Relative referencing which is the default referencing Absolute referencing Mixed Referencing  
     
    Important points
    4 type of referencing can be  cycle through f4 key -  when we are in edit mode of cell  - (use f2 to enter into edit mode) -    A1 , $a$1 , A$1, $A1 
    Shortcut Ctrl + ~  (tilde which is just above 1 in windows)
    pl download file
     
     
  23. Saurabh Jain
    hello every one,
    Today we are starting with our first tutorial, I just thought to start with creating our first workbook.
    Please see the video and then do it once on your own..
    We did the following
    1. Column headers 2. Auto filling of months 3 Formula for growth percent 4 Formatting  4 Converted into table & Added Total Row 5 Created the Chart  6 Save I am also attaching the workbook for your reference
    Please do share - What you learnt in this tutorial..
     
  25. Saurabh Jain
    These techniques cover most of what data scientists and related practitioners are using in their daily activities, whether they use solutions offered by a vendor, or whether they design proprietary tools

    The 45 data science techniques
     
    Linear Regression  Logistic Regression  Jackknife Regression * Density Estimation  Confidence Interval  Test of Hypotheses  Pattern Recognition  Clustering - (aka Unsupervised Learning) Supervised Learning  Time Series  Decision Trees  Random Numbers  Monte-Carlo Simulation  Bayesian Statistics  Naive Bayes  Principal Component Analysis - (PCA) Ensembles  Neural Networks  Support Vector Machine - (SVM) Nearest Neighbors - (k-NN) Feature Selection - (aka Variable Reduction) Indexation / Cataloguing * (Geo-) Spatial Modeling  Recommendation Engine * Search Engine * Attribution Modeling * Collaborative Filtering * Rule System  Linkage Analysis  Association Rules  Scoring Engine  Segmentation  Predictive Modeling  Graphs  Deep Learning  Game Theory  Imputation  Survival Analysis  Arbitrage  Lift Modeling  Yield Optimization Cross-Validation Model Fitting Relevancy Algorithm * Experimental Design
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