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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次
资源热度： 219
最近下载： 2024-11-29 02:58

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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