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Udemy - Complete Python & Data Science Course for Absolute Beginners

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种子名称: Udemy - Complete Python & Data Science Course for Absolute Beginners
文件类型: 视频
文件数目: 166个文件
文件大小: 10.72 GB
收录时间: 2022-9-15 05:10
已经下载: 3
资源热度: 213
最近下载: 2024-11-16 18:11

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Udemy - Complete Python & Data Science Course for Absolute Beginners.torrent
  • 001 Introduction.mp436.23MB
  • 002 Intro To Python.mp440.4MB
  • 003 Variables.mp4108.02MB
  • 004 Type Conversion Examples.mp463.79MB
  • 005 Operators.mp446.46MB
  • 006 Operators Examples.mp4126.57MB
  • 007 Collections.mp451.61MB
  • 008 Lists.mp473.31MB
  • 009 Multidimensional List Examples.mp447.68MB
  • 010 Tuples Examples.mp456.36MB
  • 011 Dictionaries Examples.mp490.91MB
  • 012 Ranges Examples.mp457.6MB
  • 013 Conditionals.mp446.77MB
  • 014 If Statement Examples.mp456.84MB
  • 015 If Statement Variants Examples.mp473.77MB
  • 016 Loops.mp449.95MB
  • 017 While Loops Examples.mp465.87MB
  • 018 For Loops Examples.mp472.16MB
  • 019 Functions.mp454.59MB
  • 020 Functions Examples.mp451.34MB
  • 021 Parameters And Return Values Examples.mp482.3MB
  • 022 Classes and Objects.mp478.5MB
  • 023 Classes Example.mp478.8MB
  • 024 Objects Examples.mp486.43MB
  • 025 Inheritance Examples.mp4133.38MB
  • 026 Static Members Example.mp483.23MB
  • 027 Summary and Outro.mp429.29MB
  • 029 00. Course Intro.mp435.01MB
  • 030 01. Intro To Pyplot.mp435.12MB
  • 031 02. Installing Matplotlib.mp435.71MB
  • 032 03. Basic Line Plot.mp458.3MB
  • 033 04. Customizing Graphs.mp485.06MB
  • 034 05. Plotting Multiple Datasets.mp470.29MB
  • 035 06. Bar Chart.mp446.01MB
  • 036 07. Pie Chart.mp461.22MB
  • 037 08. Histogram.mp465.01MB
  • 038 09. 3D Plotting.mp451.39MB
  • 039 10. Course Outro.mp426.5MB
  • 041 00. Panda Course Introduction.mp439.47MB
  • 042 01. Intro To Pandas.mp450.33MB
  • 043 02. Installing Pandas.mp435.62MB
  • 044 03. Creating Pandas Series.mp4123.1MB
  • 045 04. Date Ranges.mp463.5MB
  • 046 05. Getting Elements From Series.mp4102.44MB
  • 047 06. Getting Properties Of Series.mp470.72MB
  • 048 07. Modifying Series.mp4103.27MB
  • 049 08. Operations On Series.mp465.1MB
  • 050 09. Creating Pandas Dataframes.mp4140.11MB
  • 051 10. Getting Elements From Dataframes.mp4140.82MB
  • 052 11. Getting Properties From Dataframes.mp4111.67MB
  • 053 12. Dataframe Modification.mp4240.74MB
  • 054 13. Dataframe Operations.mp4119.06MB
  • 055 14 Dataframe Comparisons And Iteration.mp492.99MB
  • 056 15. Reading CSVs.mp479.86MB
  • 057 16.summary And Outro.mp432.62MB
  • 059 Introduction to Data Mining.mp478.62MB
  • 061 Data Wrangling Demystified.mp4576.29MB
  • 063 01. Cluster Analysis.mp4232.15MB
  • 064 02. Classification and Regression.mp4301.49MB
  • 065 03. Association and Correlation.mp4124.1MB
  • 066 04. Dimensionality Reduction.mp4271.85MB
  • 068 01. Apache Spark - An Overview Of The Framework.mp4227.92MB
  • 069 02. Spark Key Functions.mp4193.57MB
  • 070 03. Spark Machine Learning.mp491.07MB
  • 071 04. EXAMPLES - Using The Machine Learning Pipeline.mp472.51MB
  • 073 01. Text Mining.mp4160.72MB
  • 074 02. Network Mining.mp4106.57MB
  • 075 03. Matrix.mp467.34MB
  • 076 04. SQL.mp4127.47MB
  • 078 01 NLP Data Cleaning.mp476.73MB
  • 079 02. Count Vectorizer.mp477.95MB
  • 080 03. NLP Example with Spam.mp498.46MB
  • 081 04. Tweak Model with Spam Data.mp461.95MB
  • 082 05. Pipeline with Spam Data.mp449.69MB
  • 084 06. Conclusion and Challenge.mp460.68MB
  • 086 00 Project Preview.mp426.26MB
  • 087 01 What Is Apache Spark.mp413.46MB
  • 088 02 What Are Resilient Distributed Datasets.mp47.43MB
  • 089 03A What Is A Dataframe.mp48.63MB
  • 090 03B What You'll Need.mp48.64MB
  • 092 04 Start A Spark Session.mp423.55MB
  • 093 05 Load Data As A CSV.mp441.08MB
  • 094 06 Perform Basic Dataframe Operations.mp432.18MB
  • 095 07 Format Dataframe Table.mp438.95MB
  • 096 08 Perform Dataframe Math Operations.mp462.75MB
  • 097 09 Perform Dataframe Queries.mp487.99MB
  • 098 10 Build SQL Queries With Spark.mp444.19MB
  • 100 00 Project Preview.mp419.82MB
  • 101 01 Convert Csv File To A Python List.mp495.68MB
  • 102 02 Tokenize Text Data.mp4168.6MB
  • 103 03 Find Most Popular Lemmatized Words.mp492.61MB
  • 104 04 Build Dataframes Per Part Of Speech.mp434.01MB
  • 105 05 Plot Word Frequency.mp458.06MB
  • 107 00 Project Preview.mp416.89MB
  • 108 01 Load A Dataset.mp471.53MB
  • 109 02 Analyze The Main Feature.mp415.95MB
  • 110 03 Analyze Numerical Features.mp459.18MB
  • 111 04 Analyze Categorical Features.mp454.34MB
  • 113 01 Find Relationships Between Numerical Features.mp468.93MB
  • 114 02 Find Relationships Between Categorical Features.mp449.22MB
  • 115 03 Build Conditional Plots.mp448.51MB
  • 117 00 Course Overview.mp47.96MB
  • 118 01 What You'll Need.mp413.53MB
  • 120 01 Why You Must Know How To Work With Data.mp415.59MB
  • 122 01 How To Read An ER Model.mp413.99MB
  • 124 01 What Is A Database.mp421.56MB
  • 125 02 What Is A Relational Database.mp413.28MB
  • 127 01 How To Design Columns And Data Types.mp49.19MB
  • 128 02 Use Normal Forms To Check Your Design.mp427.01MB
  • 130 01 Build A SQLite Database With Python.mp434.35MB
  • 131 02 Add An Entry To The Table With SQL.mp433.01MB
  • 132 03 Add More Records To The Table.mp434.96MB
  • 133 04 Build A Second Table For Cross-Referencing.mp475.5MB
  • 134 05 Select Rows That Meet Conditions.mp446.88MB
  • 136 Course Overview.mp48.95MB
  • 137 01 Load And Create Data.mp466.55MB
  • 138 02 Perform Exploratory Data Analysis.mp427.24MB
  • 139 03 Visualize Data With Different Plots.mp457.55MB
  • 140 04 Analyze Features With More Plots.mp435.07MB
  • 141 05 Build Plots With Seaborn.mp435.42MB
  • 142 06 Build A Bokeh Plot.mp437.34MB
  • 143 07 Build A 3D Scatter Plot.mp420.07MB
  • 144 08 Rank Feature Importance.mp439.64MB
  • 145 09 Compare Positive And Negative Returns.mp435.48MB
  • 147 00 Project Preview.mp410.9MB
  • 148 01 Load Crypto Prices Dataset.mp459.82MB
  • 149 02 Visualize Bitcoin Price Trend.mp423.35MB
  • 150 03 Predict Price With Facebook Prophet.mp439.19MB
  • 151 04 Analyze Model Performance.mp474.87MB
  • 152 05 Visualize Model Results.mp426.64MB
  • 153 06 Predict Monthly Trend.mp462.1MB
  • 154 07 Predict Weekly Trend.mp436.9MB
  • 155 08 Compare Final Stock Price Of Different Strategies.mp442.98MB
  • 157 00 Project Preview.mp412.71MB
  • 158 01 Fetch Stock Data.mp457.59MB
  • 159 02 Visualize Stock Data Features.mp447.77MB
  • 160 03 Calculate Daily Return.mp424.09MB
  • 161 04 Compare Returns Of Different Stocks.mp473.48MB
  • 162 05 Compare Closing Prices.mp456.03MB
  • 164 01 Visualize Standard Deviation And Expected Returns.mp426.74MB
  • 165 02 Calculate Value At Risk.mp421.08MB
  • 166 03 Monte Carlo Analysis To Estimate Risk.mp452.01MB
  • 167 04 Visualize Price Distribution.mp460.41MB
  • 169 00 What Is Web Scraping.mp421.98MB
  • 170 01 What You'll Need.mp47.49MB
  • 172 02 Build An HTML Webpage To Scrape.mp484.26MB
  • 173 03 Select Data Structures From A Webpage.mp434.93MB
  • 174 04 Extract URLs And Text.mp438.75MB
  • 175 05 Work With Tags.mp438.63MB
  • 176 06 Work With Attributes.mp423.85MB
  • 177 07 Add Navigation To A String.mp424.29MB
  • 178 08 Navigate HTML Contents.mp461.44MB
  • 179 09 Find All Filter.mp432.42MB
  • 181 01 Project Preview.mp49.38MB
  • 182 02 What Is Plotly And Dash.mp418.69MB
  • 183 03 What You'll Need.mp410.75MB
  • 185 01 Build A Dash App.mp498.92MB
  • 186 02 Build A Graph In The Dash App.mp477.88MB
  • 188 01 Load Data From Vega Datasets.mp433.49MB
  • 189 02 Build The Layout.mp455.74MB
  • 190 03 Build A Chart With Altair.mp471.97MB
  • 192 01 Project Preview.mp415.63MB
  • 193 01 Build A Dataset.mp4141.13MB
  • 194 02 Compute Support And Confidence - If A Person Watches X, They Will Watch Y.mp464.77MB
  • 195 03 Compute Support And Confidence For All Channels.mp492.1MB
  • 196 04 Determine Which Videos Are Best To Recommend.mp467.8MB