Posted on 2018-01-02, by luongquocchinh.
Author: Jon Raasch | Publisher: Wrox | Category: Databases | Language: English | Page: 480 | ISBN: 1118847067 | ISBN13: 9781118847060 |
- Ebooks list page : 34945
- 2018-01-20[PDF] Learning Path: Haskell for Data Analysis
- 2018-01-08[PDF] A Biostatistics Toolbox for Data Analysis
- 2017-04-03[PDF] ggplot2: Elegant Graphics for Data Analysis (Use R!)
- 2018-01-19[PDF] Microsoft Office Excel 2007 Data Analysis: Your Visual Blueprint for Creating and Analyzing Data, Charts, and PivotTables
- 2018-01-05[PDF] Advanced Statistical Methods for the Analysis of Large Data-Sets (Studies in Theoretical and Applied Statistics / Selected Papers of the Statistical Societies)
- 2017-12-26[PDF] Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
- 2017-12-21[PDF] Software for Data Analysis: Programming with R (Statistics and Computing) - Removed
- 2017-11-23[PDF] Ctrl Shift Enter: A Book About Building Efficient Formulas, Advanced Formulas, and Array Formulas for Data Analysis and Calculating Problems
- 2017-11-06[PDF] Learning Python for Data Analysis and Visualization (Updated)
- 2017-10-27[PDF] Scalable Fuzzy Algorithms for Data Management and Analysis: Methods and Design (Premier Reference Source)
- 2017-02-09[PDF] Software for Data Analysis: Programming with R (Statistics and Computing) - Removed
- 2019-12-08Python Data Science: The Ultimate Handbook for Beginners on How to Explore NumPy for Numerical Data, Pandas for Data Analysis, IPython, Scikit-Learn and Tensorflow for Machine Learning and Business
- 2019-11-04Julia Programming Projects : Learn Julia 1.x by Building Apps for Data Analysis, Visualization, Machine Learning, and the Web
- 2019-10-24Learn Python for Data Analysis and Visualization
- 2019-10-04Learn Python for Data Analysis and Visualization
- 2019-09-30Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython, 1st Edition ( code)
- 2019-08-21Thoughtful Data Science; A Programmer's Toolset for Data Analysis and Artificial Intelligence with Python, Jupyter Notebook, and PixieDust
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