Udemy - Master Regression & Prediction with Pandas and Python [2025] (5.2024)

文件列表

• 1 - Introduction4 项
  • 1 - Introduction.mp4246.37 MB
  • 2 - Setup of the Anaconda Cloud Notebook.mp473.12 MB
  • 3 - Download and installation of the Anaconda Distribution optional.mp4109.69 MB
  • 4 - The Conda Package Management System optional.mp4388.86 MB
• 2 - Master Python for Data Handling21 项
  • 10 - Python Strings III DateTime Objects and Strings.mp4127.57 MB
  • 11 - Overview of Python Native Data Storage Structures.mp411.94 MB
  • 12 - Python Set.mp4135.45 MB
  • 13 - Python Tuple.mp4128.13 MB
  • 14 - Python Dictionary.mp4334.25 MB
  • 15 - Python List.mp4185.47 MB
  • 16 - Overview of Python Data Transformers and Functions.mp423.59 MB
  • 17 - Python Whileloop.mp4112.82 MB
  • 18 - Python Forloop.mp4103.49 MB
  • 19 - Python Logic Operators and conditional code branching.mp4185.49 MB
  • 20 - Python Functions I Some theory.mp419.07 MB
  • 21 - Python Functions II create your own functions.mp4178.75 MB
  • 22 - Python Object Oriented Programming I Some theory.mp4107.15 MB
  • 23 - Python Object Oriented Programming II create your own custom objects.mp4188.51 MB
  • 24 - Python Object Oriented Programming III Files and Tables.mp4343.00 MB
  • 25 - Python Object Oriented Programming IV Recap and More.mp4521.97 MB
  • 5 - Overview of Python for Data Handling.mp4269.81 MB
  • 6 - Python Integer.mp465.47 MB
  • 7 - Python Float.mp439.01 MB
  • 8 - Python Strings I.mp4127.30 MB
  • 9 - Python Strings II Intermediate String Methods.mp4174.69 MB
• 3 - Master Pandas for Data Handling42 项
  • 26 - Master Pandas for Data Handling Overview.mp4182.62 MB
  • 27 - Pandas theory and terminology.mp481.09 MB
  • 28 - Creating a Pandas DataFrame from scratch.mp4122.42 MB
  • 29 - Pandas File Handling Overview.mp411.45 MB
  • 30 - Pandas File Handling The csv file format.mp4137.30 MB
  • 31 - Pandas File Handling The xlsx file format.mp4197.71 MB
  • 32 - Pandas File Handling SQLdatabase files and Pandas DataFrame.mp467.87 MB
  • 33 - Pandas Operations Techniques Overview.mp419.36 MB
  • 34 - Pandas Operations Techniques Object Inspection.mp489.73 MB
  • 35 - Pandas Operations Techniques DataFrame Inspection.mp482.18 MB
  • 36 - Pandas Operations Techniques Column Selections.mp4113.60 MB
  • 37 - Pandas Operations Techniques Row Selections.mp480.07 MB
  • 38 - Pandas Operations Techniques Conditional Selections.mp4107.13 MB
  • 39 - Pandas Operations Techniques Scalers and Standardization.mp4154.45 MB
  • 40 - DataFrames.py0.00 MB
  • 40 - Pandas Operations Techniques Concatenate DataFrames.mp4217.48 MB
  • 41 - Pandas Operations Techniques Joining DataFrames.mp4137.05 MB
  • 41 - Pandas-Ops-Tech-Join-DF.py0.00 MB
  • 42 - Pandas Operations Techniques Merging DataFrames.mp4313.39 MB
  • 42 - Pandas-Ops-Tech-Merge-dataset.py0.00 MB
  • 43 - Pandas Operations Techniques Transpose Pivot Functions.mp4250.22 MB
  • 43 - Pandas-T-pivot-Dataset.py0.00 MB
  • 44 - Pandas Data Preparation I Overview workflow.mp463.22 MB
  • 45 - Pandas Data Preparation II Edit DataFrame labels.mp472.83 MB
  • 46 - Pandas Data Preparation III Duplicates.mp4121.62 MB
  • 47 - Pandas Data Preparation IV Missing Data Imputation.mp4450.79 MB
  • 48 - geyser.csv0.00 MB
  • 48 - geyser.xlsx0.01 MB
  • 48 - Pandas Data Preparation V Data Binnings Extra Video.mp4200.68 MB
  • 49 - Indicator-Features.py0.00 MB
  • 49 - insurance-data.csv0.06 MB
  • 49 - Pandas Data Preparation VI Indicator Features Extra Video.mp4161.46 MB
  • 50 - Pandas Data Description I Overview.mp442.86 MB
  • 51 - Pandas Data Description II Sorting and Ranking.mp486.36 MB
  • 52 - Pandas Data Description III Descriptive Statistics.mp4147.26 MB
  • 53 - Pandas Data Description IV Crosstabulations Groupings.mp4135.22 MB
  • 54 - Pandas Data Visualization I Overview.mp422.20 MB
  • 55 - Pandas Data Visualization II Histograms.mp4232.83 MB
  • 56 - Pandas Data Visualization III Boxplots.mp4120.16 MB
  • 57 - Pandas Data Visualization IV Scatterplots.mp4195.58 MB
  • 58 - Pandas Data Visualization V Pie Charts.mp4198.69 MB
  • 59 - Pandas Data Visualization VI Line plots.mp4369.29 MB
• 4 - Master Regression Models for Prediction22 项
  • 60 - Regression Prediction and Supervised Learning Section Overview I.mp4177.13 MB
  • 61 - The Traditional Simple Regression Model II.mp4227.90 MB
  • 62 - Regression-III.py0.00 MB
  • 62 - The Traditional Simple Regression Model III.mp4348.25 MB
  • 63 - Some practical and useful modelling concepts IV.mp484.61 MB
  • 64 - Some practical and useful modelling concepts V.mp483.99 MB
  • 65 - DiaB.csv0.09 MB
  • 65 - Linear Multiple Regression model VI.mp4253.00 MB
  • 65 - Multiple-Linear-Regression.py0.00 MB
  • 66 - DiaB.csv0.09 MB
  • 66 - Linear Multiple Regression model VII.mp4279.33 MB
  • 66 - Linear-Multiple-Regression-Forward-Selection.py0.00 MB
  • 67 - Multivariate Polynomial Multiple Regression models VIII.mp4101.18 MB
  • 68 - DiaB.csv0.09 MB
  • 68 - Mult-poly-regr.py0.01 MB
  • 68 - Multivariate Polynomial Multiple Regression models VIIII.mp4603.17 MB
  • 69 - insurance.csv0.05 MB
  • 69 - Regression Regularization Lasso and Ridge models X.mp4643.59 MB
  • 69 - Regularization-Ridge-Lasso-Regression.py0.01 MB
  • 70 - Decision Tree Regression models.mp4315.95 MB
  • 71 - Random Forest Regression.mp4475.51 MB
  • 72 - Voting Regression.mp4360.76 MB
• 5 - Feedforward Networks and Advanced Regression Models3 项
  • 73 - Overview.mp411.71 MB
  • 74 - Artificial Neural Networks Feedforward Networks and the MultiLayer Perceptron.mp4328.11 MB
  • 75 - Feedforward MultiLayer Perceptrons for Prediction tasks.mp4281.44 MB

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