關於 python machine learning example ，我們在網路上蒐集到這些相關的討論、資訊與評價

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- The Python Workshop
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- Web Development with Django Cookbook
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- Hands-On Exploratory Data Analysis with Python
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จ่าย $18 รับเพิ่ม
- Python Data Cleaning Cookbook
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- Machine Learning Projects for Mobile Applications
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- Hands-On Machine Learning for Cybersecurity
- Reinforcement Learning Algorithms with Python
- Hands - On Reinforcement Learning with Python - Video
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- Machine Learning Algorithms
- Python Reinforcement Learning Projects
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- Python Machine Learning, Third Edition - Third Edition
- Python Machine Learning, Second Edition - Second Edition
- Hands-On Machine Learning for Algorithmic Trading
- Hands-On Reinforcement Learning with Python
- Python Machine Learning By Example - Second Edition
- Mastering Machine Learning Algorithms
- Hands-On Natural Language Processing with Python
- Python Machine Learning Cookbook - Second Edition
- Hands-On Computer Vision with TensorFlow 2
- Feature Engineering Made Easy
- Machine Learning for Algorithmic Trading Bots with Python - Video
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อนึ่ง eBook และ Video
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อสอง ดีลนี้หมดเวลาในอีก 20 วัน
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อสาม ก็ตามชื่อแพ็คคือรวมหนังสือและวีดิโอเกี่ยวกับ Machine Learning และ Python ใครเรียนหรือทำงานด้านนี้อยู่ก็จัดกันไป
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ในวิชา "วิทยาการคำนวณ" ระดับชั้น ม. 5
ได้ดึงวิชา data science (วิทยาศาสตร์ข้อมูล)
มาปูพื้นฐานให้เด็กๆ ได้เรียนกันแล้ว นับว่าเป็นโชคดี
เพราะวิชาพวกนี้เป็นของสูง กว่าจะสัมผัสก็คงตอนป.ตรี โท เอก
...Continue ReadingIn the subject of ′′ Calculation Theology ′′ class. 5
Pulled data science (data science)
Let's master the foundation for kids to learn. It's considered lucky.
Because these subjects are high to touch. It's probably in the middle of the year. Tri To Aek

Which I will review the content to read roughly. The content is divided into 4 chapters.
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👉 ++++ Chapter 1-Information is valuable +++++
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Data science in the textbook. Used by Thai name as ′′ Information Science ′′
This chapter will mention Big Data or big data with lots of valuable information.
And so much role in this 4.0 s both public and private sector.
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If you can't imagine when you played Google search network, you'll find a lot of information that you can use in our business. This is why data science plays a very important role.
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It's not surprising that it makes the Data Scientist s' career (British name data scientist) play the most important role and charming and interesting profession of the 21th century.
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Data science, if in the book, he defines it
′′ Study of the process, method or technique to process enormous amounts of data to process to obtain knowledge, understand phenomena, or interpret prediction or prediction, find out patterns or trends from information.
and can be analysed to advise the right choice or take decision for maximum benefit
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For Data science work, he will have the following steps.
- Questioning my own interest.
- Collect information.
- Data Survey
- Data Analysis (analyze the data)
- Communication and Results Visualization (Communicate and visualize the results)
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🤔 Also he talks about design thinking... but what is it?
Must say the job of a data scientist
It doesn't end just taking the data we analyzed.
Let's show people how to understand.
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The application design process is still required.
To use data from our analytics
The word design thinking is the idea. The more good designer it is.
Which Data Scientists Should Have To Design Final Applications
Will meet user demand
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👉 ++++ Chapter 2 Collection and Exploration +++++
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This chapter is just going to base.
2.1 Collection of data
In this chapter, I will talk about information that is a virtual thing.
We need to use this internet.

2.2 Data preparation (data preparation)
Content will be available.
- Data Cleaning (data cleansing)
- Data Transformation (data transformation)
In the university. 5 is not much but if in college level, you will find advanced technique like PCA.
- Info Link (combining data)

2.3 Data Exploration (data exploration)
Speaking of using graphs, let's explore the information e
Histogram graph. Box plot diagram (box plot). Distributed diagram (scatter plot)
With an example of programming, pulls out the plot to graph from csv (or xls) file.

2.4 Personal Information
For this topic, if a data scientist is implementing personal data, it must be kept secret.
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Where the issues of personal information are now available. Personal Data Protection is Done
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👉 ++++ Chapter 3 Data Analysis ++++
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Divided into 2 parts:
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3.1 descriptive analysis (descriptive analytics)
Analyzing using the numbers we've studied since
- Proportion or percentage
- Medium measurement of data, average, popular base.
Correlation (Correlation) relationship with programming is easy.
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3.2 predictive analysis (predictive analytics)
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- numeric prediction is discussed. (numeric prediction)
- Speaking of technique linear regression, a straight line equation that will predict future information.
Including sum of squared errors
Let's see if the straight line graph is fit with the information. (with programming samples)
- Finally mentioned K-NN (K-Nearest Neighbors: K-NN) is the closest way to finding K-N-Neighborhood for classification (Category)

*** Note *****
linear regression กับ K-NN
This is also an algorithm. One of the machine learning (machine learning, one branch of AI)
Kids in the middle of the day, I get to study.
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👉 +++ Chapter 4 Making information pictured and communicating with information +++
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This chapter doesn't matter much. Think about the scientist after analyzing what data is done. The end is showing it to other people by doing data visualization. (Better summoning)
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In contents, it's for example using a stick chart, line chart, circular chart, distribution plan.
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The last thing I can't do is tell a story from information (data story telling) with a message. Be careful when you present information.
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*** this note ***
😗 Program language which textbooks mentioned and for example.
It's also python and R language
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For R language, many people may not be familiar.
The IT graduate may be more familiar with Python.
But anyone from the record line will surely be familiar.
Because R language is very popular in statistical line
And it can be used in data science. Easy and popular. Python
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But if people from data science move to another line of AI
It's deep learning (deep learning)
Python will be popular with eating.
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😓 Ending. Even I wrote a review myself, I still feel that.
- The university. 5 is it going to be hard? Can a child imagine? What did she do?
- Or was it right that I packed this course into Big Data era?
You can comment.
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But for sure, both parents and teachers are tired.
Because it's a new content. It's real.
Keep fighting. Thai kids 4.0
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Note in the review section of the university's textbook. 4 There will be 3 chapters. Read at.
https://www.facebook.com/programmerthai/photos/a.1406027003020480/2403432436613260/?type=3&theater
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++++++++++++++++++++
Before leaving, let's ask for publicity.
++++++++++++++++++++
Recommend the book ′′ Artificial Intelligence (AI) is not difficult ′′
It can be understood by the number. End of book 1 (Thai language content)
Best seller ranked
In the MEB computer book category.
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The contents will describe Artificial Intelligence (A) in view of the number. The end.
Without a code of dizzy
With colorful illustrations to see, easy to read.
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If you are interested, you can order.
👉 https://www.mebmarket.com/web/index.php?action=BookDetails&data=YToyOntzOjc6InVzZXJfaWQiO3M6NzoiMTcyNTQ4MyI7czo3OiJib29rX2lkIjtzOjY6IjEwODI0NiI7fQ&fbclid=IwAR11zxJea0OnJy5tbfIlSxo4UQmsemh_8TuBF0ddjJQzzliMFFoFz1AtTo4
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Personal like the book. You can see this link.
👉 https://www.dropbox.com/s/fg8l38hc0k9b0md/chapter_example.pdf?dl=0
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Sorry, paper book. I don't have it yet. Sorry.
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✍ Written by Thai programmer thai progammerTranslated