Python machine learning: a complete guide for beginners on machine learning and deep learning with Python
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
[Erscheinungsort nicht ermittelbar]
[Andrew Park]
[2020]
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | 125 Seiten Illustrationen, Diagramme |
| ISBN: | 9781676467687 |
Internformat
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Datensatz im Suchindex
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| adam_text | Table of Contents INTRODUCTION................................................................... .....5 CHAPTER 1։ WHAT IS MACHINE LEARNING?................................9 Applications of Machine Learning........................................................... 12 Advantages and Disadvantages of Machine Learning.........................14 CHAPTER 2: MACHINE LEARNING - CONCEPTS TERMS.... 16 Objectives of Machine Learning.............................................................. 19 Categories of Machine Learning Systems.......................................... 20 Steps in building a Machine Learning System....... ...............................25 CHAPTER 3։ LINEAR REGRESSION WITH PYTHON...................29 Linear regression with one variable...................................................... 29 CHAPTER 4: LISTS IN PYTHON...........................................................35 Nested Lists.................. 35 MMARY of List Methods in Python............................................................41 Inbuilt Python Functions to manipulate Python Lists.......................42 CHAPTER 5: MODULES IN PYTHON.................................................43 Modules Concept and Utility Within Python.......................................43 CHAPTER 6: MACHINE LEARNING TRAINING MODEL............58 Simple Machine Learning Training Model in Python......................... 59 Simple Machine Learning Python Model using Linear Regression..61 CHAPTER 7։ CONDITIONAL OR DECISION STATEMENTS.......64 Conditional Tests in
Python..................................................................... 65 Creating Multiple Conditions..................................................................69 If Statements...................................................................................... 74 CHAPTER 8:ESSENTIAL LIBRARIES FOR MACHINE LEARNING IN PYTHON..........................................................................85 Scikit-Learn...............................................................................................86 TensorFlow.................................................................................................. 86 Theano................. 87 Pandas............................................................................................................ 88 Matplotlib.................................................................................................... 90 3
Seaborn.......................................................................................................... 92 NumPy............................................................................................................. 94 SciPy............................................................................. 94 Keras.............................................................................................................. 95 PyTorch..................... 96 Scrapy............................................................................................................. 96 Statsmodels..................................................................................................96 CHAPTER 9:WHAT IS THE TENSORFLOW LIBRARY................ 98 Installing TensorFlow............................................................................ 100 Activate tensorenviron........................................................................... 104 CHAPTER 10 :ARTIFICIAL NEURAL NETWORKS....................... 107 Definition of artificial neural network............................................. 107 What are the types of artificial neural networks?...........................116 HOW TO TRAIN AN ARTIFICIAL NEURAL NETWORK?................................................. Il8 Artificial neural network: pros and cons of use................................122 CONCLUSION...........................................................................................124 4
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| adam_txt |
Table of Contents INTRODUCTION. .5 CHAPTER 1։ WHAT IS MACHINE LEARNING?.9 Applications of Machine Learning. 12 Advantages and Disadvantages of Machine Learning.14 CHAPTER 2: MACHINE LEARNING - CONCEPTS TERMS. 16 Objectives of Machine Learning. 19 Categories of Machine Learning Systems. 20 Steps in building a Machine Learning System. .25 CHAPTER 3։ LINEAR REGRESSION WITH PYTHON.29 Linear regression with one variable. 29 CHAPTER 4: LISTS IN PYTHON.35 Nested Lists. 35 MMARY of List Methods in Python.41 Inbuilt Python Functions to manipulate Python Lists.42 CHAPTER 5: MODULES IN PYTHON.43 Modules Concept and Utility Within Python.43 CHAPTER 6: MACHINE LEARNING TRAINING MODEL.58 Simple Machine Learning Training Model in Python. 59 Simple Machine Learning Python Model using Linear Regression.61 CHAPTER 7։ CONDITIONAL OR DECISION STATEMENTS.64 Conditional Tests in
Python. 65 Creating Multiple Conditions.69 If Statements. 74 CHAPTER 8:ESSENTIAL LIBRARIES FOR MACHINE LEARNING IN PYTHON.85 Scikit-Learn.86 TensorFlow. 86 Theano. 87 Pandas. 88 Matplotlib. 90 3
Seaborn. 92 NumPy. 94 SciPy. 94 Keras. 95 PyTorch. 96 Scrapy. 96 Statsmodels.96 CHAPTER 9:WHAT IS THE TENSORFLOW LIBRARY. 98 Installing TensorFlow. 100 Activate tensorenviron. 104 CHAPTER 10 :ARTIFICIAL NEURAL NETWORKS. 107 Definition of artificial neural network. 107 What are the types of artificial neural networks?.116 HOW TO TRAIN AN ARTIFICIAL NEURAL NETWORK?. Il8 Artificial neural network: pros and cons of use.122 CONCLUSION.124 4 |
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| discipline | Informatik |
| discipline_str_mv | Informatik |
| format | Book |
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| index_date | 2024-07-03T17:25:12Z |
| indexdate | 2024-07-10T09:08:25Z |
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| isbn | 9781676467687 |
| language | English |
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| physical | 125 Seiten Illustrationen, Diagramme |
| publishDate | 2020 |
| publishDateSearch | 2020 |
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| publisher | [Andrew Park] |
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| spelling | Park, Andrew Verfasser aut Python machine learning a complete guide for beginners on machine learning and deep learning with Python Andrew Park [Erscheinungsort nicht ermittelbar] [Andrew Park] [2020] 125 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Python Programmiersprache (DE-588)4434275-5 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Python Programmiersprache (DE-588)4434275-5 s Maschinelles Lernen (DE-588)4193754-5 s DE-604 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032710267&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Park, Andrew Python machine learning a complete guide for beginners on machine learning and deep learning with Python Python Programmiersprache (DE-588)4434275-5 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
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| title | Python machine learning a complete guide for beginners on machine learning and deep learning with Python |
| title_auth | Python machine learning a complete guide for beginners on machine learning and deep learning with Python |
| title_exact_search | Python machine learning a complete guide for beginners on machine learning and deep learning with Python |
| title_exact_search_txtP | Python machine learning a complete guide for beginners on machine learning and deep learning with Python |
| title_full | Python machine learning a complete guide for beginners on machine learning and deep learning with Python Andrew Park |
| title_fullStr | Python machine learning a complete guide for beginners on machine learning and deep learning with Python Andrew Park |
| title_full_unstemmed | Python machine learning a complete guide for beginners on machine learning and deep learning with Python Andrew Park |
| title_short | Python machine learning |
| title_sort | python machine learning a complete guide for beginners on machine learning and deep learning with python |
| title_sub | a complete guide for beginners on machine learning and deep learning with Python |
| topic | Python Programmiersprache (DE-588)4434275-5 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Python Programmiersprache Maschinelles Lernen |
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