Python for data analysis: how to use Python and data science to better understand, summarize, and investigate your data
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
[Erscheinungsort nicht ermittelbar]
Andrew Park
[2021]
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | 100 Seiten Diagramme |
| ISBN: | 9781801779562 |
Staff View
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| adam_text | Python for Data Analysis Table of Contents INTRODUCTION...................................................................................... 6 CHAPTER l: WHAT IS THE TENSORFLOW LIBRARY..............8 Installing TensorFlow...........................................................................ю Activate tensorenviron..........................................................................16 CHAPTER 2: ARTIFICIAL NEURAL NETWORKS.......................20 Definition of artificial neural network.......................................... 20 Example of an artificial neural network.......................................21 What is an activation function and its role in neural network models?.......................................................................................... 22 The sigmoid function..................................................................... 25 The tanh junction.......................................................................... 27 The ReLu function......................................................................... 27 The Softmaxfunction.................................................................... 29 What are the types of artificial neural networks?........................ 31 How TO train an artificial neural network?.................................... 34 Artificial neural network: pros and cons of use............................ 38 CHAPTER 3: HISTORY OF DATA SCIENCE..................................40 CHAPTER 4: WORKING WITH PYTHON FOR DATA SCIENCE
........................................................................................... 46 Why Is Python Important?.....................................................................46 What Is Python?...................................................................................... 48 The Role of Python in Data Science....................................................49 Data Cleaning................................................................................49 Data Visualization.........................................................................50 Feature ExԾaction........................................................................50 Model Building..............................................................................50 Python Installation................................................................................51 Installation Under Windows.............................................................. 52 Conda............................................................................................ 53 Spyder........................................................................................... 53 Installation Under MAC.......................................................................53 Installation Under Linux......................................................................54 Install Python................................................................................54 Python Engineering Structure........................................................... 57 CHAPTER 5: MACHINE LEARNING AND HOW IT FITS WITH DATA
SCIENCE......................................................................................60 What is Machine Learning?...................................................................62 řv Չ N»
Python for Data Analysis CHAPTER 6:DATA STRUCTURES OBJECT-ORIENTED PYTHON ........................................................................................... 66 Immutable structured data (static)......................................................67 Character string - Indexing or access and sequence length........67 Trimming or slicing sequences and other operations..................... 69 Strings are immutable.............................................................................. 71 Examples...................................................................................................... 73 Tuples................................................................................................................ 77 Indexing, trimming and other tuple operations............................... 79 Multiple assignments and fimetions with multiple returns.......... 81 Tuple Methods...............................................................................................84 Zip function.................................................................................................... 85 Frozen sets (Frozen set)............................................................................86 Types of structured mutable (dynamic) data.................................... 87 Lists................................................................................................................87 Indexing, trimming and other list operations.................................. 89 Objects, values and references................................................................
91 Object-oriented programming with Python.......................................94 CONCLUSION..................................................................................... 100 ~4~
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| adam_txt |
Python for Data Analysis Table of Contents INTRODUCTION. 6 CHAPTER l: WHAT IS THE TENSORFLOW LIBRARY.8 Installing TensorFlow.ю Activate tensorenviron.16 CHAPTER 2: ARTIFICIAL NEURAL NETWORKS.20 Definition of artificial neural network. 20 Example of an artificial neural network.21 What is an activation function and its role in neural network models?. 22 The sigmoid function. 25 The tanh junction. 27 The ReLu function. 27 The Softmaxfunction. 29 What are the types of artificial neural networks?. 31 How TO train an artificial neural network?. 34 Artificial neural network: pros and cons of use. 38 CHAPTER 3: HISTORY OF DATA SCIENCE.40 CHAPTER 4: WORKING WITH PYTHON FOR DATA SCIENCE
. 46 Why Is Python Important?.46 What Is Python?. 48 The Role of Python in Data Science.49 Data Cleaning.49 Data Visualization.50 Feature ExԾaction.50 Model Building.50 Python Installation.51 Installation Under Windows. 52 Conda. 53 Spyder. 53 Installation Under MAC.53 Installation Under Linux.54 Install Python.54 Python Engineering Structure. 57 CHAPTER 5: MACHINE LEARNING AND HOW IT FITS WITH DATA
SCIENCE.60 What is Machine Learning?.62 řv Չ N»
Python for Data Analysis CHAPTER 6:DATA STRUCTURES OBJECT-ORIENTED PYTHON . 66 Immutable structured data (static).67 Character string - Indexing or access and sequence length.67 Trimming or slicing sequences and other operations. 69 Strings are immutable. 71 Examples. 73 Tuples. 77 Indexing, trimming and other tuple operations. 79 Multiple assignments and fimetions with multiple returns. 81 Tuple Methods.84 Zip function. 85 Frozen sets (Frozen set).86 Types of structured mutable (dynamic) data. 87 Lists.87 Indexing, trimming and other list operations. 89 Objects, values and references.
91 Object-oriented programming with Python.94 CONCLUSION. 100 ~4~ |
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| title | Python for data analysis how to use Python and data science to better understand, summarize, and investigate your data |
| title_auth | Python for data analysis how to use Python and data science to better understand, summarize, and investigate your data |
| title_exact_search | Python for data analysis how to use Python and data science to better understand, summarize, and investigate your data |
| title_exact_search_txtP | Python for data analysis how to use Python and data science to better understand, summarize, and investigate your data |
| title_full | Python for data analysis how to use Python and data science to better understand, summarize, and investigate your data Andrew Park |
| title_fullStr | Python for data analysis how to use Python and data science to better understand, summarize, and investigate your data Andrew Park |
| title_full_unstemmed | Python for data analysis how to use Python and data science to better understand, summarize, and investigate your data Andrew Park |
| title_short | Python for data analysis |
| title_sort | python for data analysis how to use python and data science to better understand summarize and investigate your data |
| title_sub | how to use Python and data science to better understand, summarize, and investigate your data |
| topic | Python Programmiersprache (DE-588)4434275-5 gnd Datenanalyse (DE-588)4123037-1 gnd |
| topic_facet | Python Programmiersprache Datenanalyse |
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