PushBT Magnet/Torrent

Categories

Recommend Tools

  • Convert torrent to magnet
  • Convert torrent to magnet

filePackt-Python-SQL-Tableau-1vVxd

Packt Python SQL Tableau Integrating Python SQL and Tableau FCO
  • MP401.Introduction/0101.What Does the Course Cover.mp439.50MB
  • MP402.What is software integration/0201.Properties and Definitions Data, Servers, Clients, Requests and Responses.mp430.27MB
  • MP402.What is software integration/0202.Properties and Definitions Data Connectivity, APIs, and Endpoints.mp456.20MB
  • MP402.What is software integration/0203.Further Details on APIs.mp455.78MB
  • MP402.What is software integration/0204.Text Files as Means of Communication.mp429.46MB
  • MP402.What is software integration/0205.Definitions and Applications.mp433.90MB
  • MP403.Setting up the working environment/0301.Setting Up the Environment - An Introduction (Do Not Skip, Please)!.mp44.92MB
  • MP403.Setting up the working environment/0302.Why Python and why Jupyter.mp435.26MB
  • MP403.Setting Anaconda.mp430.36MB
  • MP403.Setting up the working environment/0304.The Jupyter Dashboard - Part 1.mp46.77MB
  • MP403.Setting up the working environment/0305.The Jupyter Dashboard - Part 2.mp414.39MB
  • MP403.Setting sklearn.mp47.93MB
  • MP404.What's next in the course/0401.Up Ahead.mp425.84MB
  • MP404.What's next in the course/0402.Real-Life Example Absenteei at Work.mp425.54MB
  • MP404.What's next in the course/0403.Real-Life Example The Dataset.mp425.81MB
  • MP405.Preprocessing/0501.Data Sets in Python.mp413.03MB
  • MP405.Preprocessing/0502.Data at a Glance.mp439.36MB
  • MP405.Preprocessing/0503.A Note on Our Usage of Terms with Multiple Meanings.mp420.06MB
  • MP405.Preprocessing/0504.Picking the Appropriate Approach for the Task at Hand.mp410.93MB
  • MP405.Preprocessing/0505.Removing Irrelevant Data.mp434.34MB
  • MP405.Preprocessing/0506.Examining the Reasons for Absence.mp420.25MB
  • MP405.Preprocessing/0507.Splitting a Column into Multiple Dummies.mp446.70MB
  • MP405.Preprocessing/0508.Dummy Variables and Their Statistical Importance.mp45.75MB
  • MP405.Preprocessing/0509.Grouping - Transforming Dummy Variables into Categorical Variables.mp438.49MB
  • MP405.Preprocessing/0510.Concatenating Columns in Python.mp418.38MB
  • MP405.Preprocessing/0511.Changing Column Order in Pandas DataFrame.mp46.94MB
  • MP405.Preprocessing/0512.Implementing Checkpoints in Coding.mp413.01MB
  • MP405.Preprocessing/0513.Exploring the Initial Date Column.mp426.59MB
  • MP405.Preprocessing/0514.Using the Date Column to Extract the Appropriate Month Value.mp424.11MB
  • MP405.Preprocessing/0515.Introducing Day of the Week.mp415.08MB
  • MP405.Preprocessing/0516.Further Analysis of the DataFrame Next 5 Columns.mp414.11MB
  • MP405.Preprocessing/0517.Further Analysis of the DaraFrame Education, Children, Pets.mp418.79MB
  • MP405.Preprocessing/0518.A Final Note on Preprocessing.mp422.05MB
  • MP406.chine Learnings/0601.Exploring the Problem from a Machine Learning Point of View.mp425.50MB
  • MP406.chine Learnings/0602.Creating the Targets for the Logistic Regression.mp434.39MB
  • MP406.chine Learnings/0603.Selecting the Inputs.mp412.26MB
  • MP406.chine Learnings/0604.A Bit of Statistical Preprocessing.mp415.62MB
  • MP406.chine Learnings/0605.Train-test Split of the Data.mp439.92MB
  • MP406.chine Learnings/0606.Training the Model and Assessing its Accuracy.mp432.65MB
  • MP406.chine Learnings/0607.Extracting the Intercept and Coefficients from a Logistic Regression.mp433.39MB
  • MP406.chine the Logistic Regression Coefficients.mp446.47MB
  • MP406.chine Learnings/0609.Omitting the dummy variables from the Standardization.mp433.87MB
  • MP406.chine the Important Predictors.mp428.11MB
  • MP406.chine Learnings/0611.Simplifying the Model (Backward Elimination).mp437.87MB
  • MP406.chine Learnings/0612.Testing the Machine Learning Model.mp441.45MB
  • MP406.chine Learnings/0613.How to Se the Machine Learning Model and Prepare it for Future Deployment.mp430.40MB
  • MP406.chine Learnings/0614.Creating a Module for Later Use of the Model.mp449.61MB
  • MP407.Installing MySQL.mp449.73MB
  • MP407.Installing MySQL and Getting Acquainted with the Interface/0702.Setting Up a Connection.mp49.54MB
  • MP407.Installing to the MySQL Interface.mp417.82MB
  • MP408.Connecting Python and SQL/0801.Implementing the 'absenteei_module' - Part I.mp415.57MB
  • MP408.Connecting Python and SQL/0802.Implementing the 'absenteei_module' - Part II.mp428.36MB
  • MP408.Connecting Python and SQL/0803.Creating a Database in MySQL.mp433.46MB
  • MP408.Connecting Python and SQL/0804.Importing and Installing 'pymysql'.mp411.17MB
  • MP408.Connecting Python and SQL/0805.Creating a Connection and Cursor.mp410.44MB
  • MP408.Connecting Python and SQL/0806.Creating the 'predicted_outputs' table in MySQL.mp427.40MB
  • MP408.Connecting Python and SQL/0807.Running an SQL SELECT Statement from Python.mp412.54MB
  • MP408.Connecting Python and SQL/0808.Transferring Data from Jupyter to Workbench - Part I.mp445.36MB
  • MP408.Connecting Python and SQL/0809.Transferring Data from Jupyter to Workbench - Part II.mp432.11MB
  • MP408.Connecting Python and SQL/0810.Transferring Data from Jupyter to Workbench - Part III.mp422.42MB
  • MP409.Analyzing the Obtained data in Tableau/0901.Analysis in Tableau Age vs Probability.mp426.42MB
  • MP409.Analyzing the Obtained data in Tableau/0902.Analysis in Tableau Reasons vs Probability.mp430.18MB
  • MP409.Analyzing the Obtained data in Tableau/0903.Analysis in Tableau Transportation Expense vs Probability.mp466.99MB
  • ZIPExercise Files/exercise_files.zip12.01MB
Latest Search: 1.CRAD-066   2.IDBD-209   3.LADY-054   4.PCM-051   5.TYWD-013   6.DAZD-031   7.FETI-025   8.DJSI-004   9.XV-149   10.MXSPS-231   11.MIAD-498   12.PBD-187   13.MIRD-099   14.RKI-057   15.JUSD-365   16.HYAZ-002   17.ZONO-057   18.ONSD-640   19.CRPD-392   20.ESL-016   21.KWBD-041   22.ONSD-421   23.CWM-128   24.VENU-360   25.WING-010   26.ONSD-549   27.ONSD-494   28.ONSD-469   29.PBD-118   30.AAJB-002   31.ONSD-350   32.IPTD-024   33.MIBD-457   34.ZOS-009   35.KK-062   36.WANZ-044   37.IDBD-087   38.MIBD-423   39.DJNE-52   40.MXSPS-026   41.KVS-002   42.BIB-053   43.TDMJ-55   44.MGDV-002   45.CADV-195   46.MIBD-740   47.SCF-036   48.TBL-081   49.HFD-17   50.JFB-045   51.MAST-040   52.MXGS-529   53.SXXP-004   54.DLTM-006   55.DSE-506   56.FAX-391   57.MXGS-520   58.MAMA-354   59.QXL-91   60.DZR-04   61.RD-390   62.MIRA-004   63.LHYL-003   64.UGUG-034   65.JKFI-030   66.AECB-100   67.MVF-006   68.KND-003   69.IT-035   70.M-823   71.066   72.209   73.054   74.051   75.013   76.031   77.025   78.004   79.149   80.231   81.498   82.187   83.099   84.057   85.365   86.002   87.057   88.0   89.392   90.016   91.041   92.421   93.128   94.360   95.010   96.549   97.494   98.469   99.118   100.002   101.350   102.024   103.457   104.009   105.062   106.044   107.087   108.423   109.52   110.026   111.002   112.053   113.55   114.002   115.195   116.740   117.036   118.081   119.17   120.045   121.040   122.529   123.004   124.006   125.506   126.391   127.520   128.354   129.91   130.04   131.390   132.004   133.003   134.034   135.030   136.100   137.006   138.003   139.035   140.823