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Master Cluster Analysis with Python and Pandas [2025]

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Master Cluster Analysis and Unsupervised Learning with Pandas and Python for Data Science and Machine Learning [2025]


1 - Introduction
  • 1 - Introduction
  • 2 - Setup of the Anaconda Cloud Notebook
  • 3 - Download and installation of the Anaconda Distribution optional
  • 4 - The Conda Package Management System optional

  • 2 - Master Python for Data Handling
  • 5 - Overview of Python for Data Handling
  • 6 - Python Integer
  • 7 - Python Float
  • 8 - Python Strings I
  • 9 - Python Strings II Intermediate String Methods
  • 10 - Python Strings III DateTime Objects and Strings
  • 11 - Overview of Python Native Data Storage Structures
  • 12 - Python Set
  • 13 - Python Tuple
  • 14 - Python Dictionary
  • 15 - Python List
  • 16 - Overview of Python Data Transformers and Functions
  • 17 - Python Whileloop
  • 18 - Python Forloop
  • 19 - Python Logic Operators and conditional code branching
  • 20 - Python Functions I Some theory
  • 21 - Python Functions II create your own functions
  • 22 - Python Object Oriented Programming I Some theory
  • 23 - Python Object Oriented Programming II create your own custom objects
  • 23 - python-oop-ii.zip
  • 24 - Python Object Oriented Programming III Files and Tables
  • 24 - python-oop3.zip
  • 25 - Python Object Oriented Programming IV Recap and More
  • 25 - Text-file.txt
  • 25 - python-oop4-recap.zip

  • 3 - Master Pandas for Data Handling
  • 26 - Master Pandas for Data Handling Overview
  • 27 - Pandas theory and terminology
  • 28 - Creating a Pandas DataFrame from scratch
  • 29 - Pandas File Handling Overview
  • 30 - Pandas File Handling The csv file format
  • 31 - Pandas File Handling The xlsx file format
  • 32 - Pandas File Handling SQLdatabase files and Pandas DataFrame
  • 33 - Pandas Operations Techniques Overview
  • 34 - Pandas Operations Techniques Object Inspection
  • 35 - Pandas Operations Techniques DataFrame Inspection
  • 36 - Pandas Operations Techniques Column Selections
  • 37 - Pandas Operations Techniques Row Selections
  • 38 - Pandas Operations Techniques Conditional Selections
  • 39 - Pandas Operations Techniques Scalers and Standardization
  • 40 - Pandas Operations Techniques Concatenate DataFrames
  • 40 - dataframes.zip
  • 41 - Pandas Operations Techniques Joining DataFrames
  • 41 - pandas-ops-tech-join-df.zip
  • 42 - Pandas Operations Techniques Merging DataFrames
  • 42 - pandas-ops-tech-merge-dataset.zip
  • 43 - Pandas Operations Techniques Transpose Pivot Functions
  • 43 - pandas-t-pivot-dataset.zip
  • 44 - Pandas Data Preparation I Overview workflow
  • 45 - Pandas Data Preparation II Edit DataFrame labels
  • 46 - Pandas Data Preparation III Duplicates
  • 47 - Pandas Data Preparation IV Missing Data Imputation
  • 48 - Pandas Data Preparation V Data Binnings Extra Video
  • 48 - geyser.csv
  • 48 - geyser.xlsx
  • 49 - Pandas Data Preparation VI Indicator Features Extra Video
  • 49 - indicator-features.zip
  • 49 - insurance-data.csv
  • 50 - Pandas Data Description I Overview
  • 51 - Pandas Data Description II Sorting and Ranking
  • 52 - Pandas Data Description III Descriptive Statistics
  • 53 - Pandas Data Description IV Crosstabulations Groupings
  • 54 - Pandas Data Visualization I Overview
  • 55 - Pandas Data Visualization II Histograms
  • 56 - Pandas Data Visualization III Boxplots
  • 57 - Pandas Data Visualization IV Scatterplots
  • 58 - Pandas Data Visualization V Pie Charts
  • 59 - Pandas Data Visualization VI Line plots

  • 4 - Master Cluster Analysis and Unsupervised Learning
  • 60 - Overview
  • 61 - KMeans Cluster Analysis
  • 61 - iris.csv
  • 61 - kmeans-cluster-analysis.zip
  • 62 - Autoupdated KMeans Cluster Analysis introduction and simulation
  • 62 - au-kmeans-cluster-analysis-simulation.zip
  • 62 - penguins.csv
  • 63 - DensityBased Spatial Clustering of Applications with Noise DBSCAN
  • 63 - dbscan.zip
  • 64 - Four Hierarchical Clustering algorithms
  • 64 - agglo-clustering.zip
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    شناسه: 43322
    حجم: 11133 مگابایت
    مدت زمان: 1602 دقیقه
    تاریخ انتشار: ۶ بهمن ۱۴۰۳
    دسته بندی محصول
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