ลือ ! Carl Pei หนึ่งในผู้ก่อตั้ง OnePlus อาจลาออกจากบริษัทแล้ว
Rumors! Carl Pei, one of the founders of OnePlus may have resigned from the company.Translated
ลือ ! Carl Pei หนึ่งในผู้ก่อตั้ง OnePlus อาจลาออกจากบริษัทแล้ว
.
สื่อ Android Police รายงานจากชาว Reddit นามว่า JonSigur ได้อัปโหลดภาพเปิดเผยรายชื่อหัวหน้าหน่วยงานต่าง ๆ ใน OnePlus โดยมีจุดสังเกตว่า Carl Pei หนึ่งในผู้ก่อตั้ง OnePlus ไม่ได้ติดรายชื่อหัวหน้าหน่วยงานใดหน่วยงานหนึ่งเลย
.
นอกจากนี้ Emily Dai หนึ่งในผู้บริหาร OnePlus ในสาขาประเทศอินเดีย ก็ได้รับตำแหน่งเป็นหัวหน้าสายการผลิตมือถือรุ่น Nord จากเดิมก่อนหน้านี้ Pei เคยรับตำแหน่งเป็นหัวหน้าสายการผลิต ทำให้หลายคนคาดเดาว่า Carl Pei อาจจะออกจากบริษัทไปแล้ว
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Android Police ได้ลองติดต่อกับบริษัท OnePlus โดยตรง ซึ่งฝ่ายโฆษก OnePlus ก็ออกมาปฏิเสธที่จะแสดงความคิดเห็นเกี่ยวกับข่าวครั้งนี้ จึงมีความเป็นไปได้สูงที่ข่าวลือ Carl Pei ออกจากบริษัท OnePlus นั้นเป็นเรื่องจริง
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อย่างไรก็ตาม Pete Lau รองผู้ก่อตั้ง OnePlus ยังคงดำรงตำแหน่งเป็นผู้บริหารของบริษัทต่อไป ส่วนสื่อ TechCrunch ได้รายงานจาก "แหล่งข่าวที่น่าเชื่อถือ" เพิ่มเติมว่า Carl Pei ลาออกจาก OnePlus เพื่อต้องการ "สร้างกิจการของเขาเอง" ในขณะที่ทางบริษัท OnePlus ยังคงไม่มีการแถลงการณ์เกี่ยวกับข่าวลือครั้งนี้
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ที่มา: https://www.androidpolice.com/…/it-sure-looks-like-oneplus…/
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https://www.reddit.com/…/…/carl_pei_has_left_oneplus_sacked/
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#ข่าวเกม #GamingDose #OnePlus
Rumors! Carl Pei, one of the founders of OnePlus may have resigned from the company.
.
The Reddit Reddit Media Reported by Android Police Report, JonSigur, uploaded a photo to reveal the list of Chiefs of Staff in OnePlus, noted that Carl Pei, one of the Founders of OnePlus, didn't get a list of any of the agencies chiefs.
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In addition, Emily Dai, one of the OnePlus executives in Indian branch, has been named as Nord mobile phone line chief from previously. Pei has been named as production line chief. Many people predict Carl Pei may have left the company.
.
Android Police has tried direct contact with OnePlus company, OnePlus spokesman refuses to comment on this news. There is a high chance that Carl Pei left OnePlus company.
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However, Pete Lau, Deputy Founders, OnePlus continues to be executive director of the company. TechCrunch media has reported from ′′ more trustworthy news sources that Carl Pei resigns from OnePlus to want to ′′ build his own affairs While OnePlus company still has no statement about. This rumor.
.
Source: https://www.androidpolice.com/2020/10/12/it-sure-looks-like-oneplus-co-founder-carl-pei-has-left-the-company/
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https://www.reddit.com/r/oneplus/comments/j9oas0/carl_pei_has_left_oneplus_sacked/
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#ข่าวเกม #GamingDose #OnePlusTranslated
同時也有3部Youtube影片,追蹤數超過244萬的網紅メンタリスト DaiGo,也在其Youtube影片中提到,📘この動画内で紹介したおすすめ動画・ニコニコ動画は 知識のNetflix【Dラボ】で見放題! 今なら20日間無料→https://daigovideolab.jp/ 🐈 【恐怖と欲望の説得術】歴史を動かした偉人の話し方 【前編】https://www.nicovideo.jp/watch/1589...
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r predict 在 資策會 Facebook 的最讚貼文
【Job Description/工作內容】
1.Data Cleaning and Analysis, thus training AI to classify, predict, and recommend items or issues./數據清理與分析、社群分析、回歸與分類、預測、推薦系統。
2.Field Application: manufacturing, healthcare, green energy, fintech /領域應用:製造、健康照護、綠能、金融等領域。
【Required Qualifications/應具備程式語言能力】
Must Skills: Java, Python, R,
【Education/學歷要求】
Master/碩士
r predict 在 โปรแกรมเมอร์ไทย Thai programmer Facebook 的最佳解答
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.
.
👉 ++++ Chapter 1-Information is valuable +++++
.
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.
.
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.
.
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.
.
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
.
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)
.
🤔 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.
.
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
.
👉 ++++ Chapter 2 Collection and Exploration +++++
.
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.
.
Where the issues of personal information are now available. Personal Data Protection is Done
.
.
👉 ++++ Chapter 3 Data Analysis ++++
.
Divided into 2 parts:
.
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.
.
.
3.2 predictive analysis (predictive analytics)
.
- 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.
.
.
👉 +++ Chapter 4 Making information pictured and communicating with information +++
.
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)
.
In contents, it's for example using a stick chart, line chart, circular chart, distribution plan.
.
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.
.
.
.
*** this note ***
😗 Program language which textbooks mentioned and for example.
It's also python and R language
.
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
.
But if people from data science move to another line of AI
It's deep learning (deep learning)
Python will be popular with eating.
.
.
#########
😓 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.
.
But for sure, both parents and teachers are tired.
Because it's a new content. It's real.
Keep fighting. Thai kids 4.0
.
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
.
++++++++++++++++++++
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.
.
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.
.
If you are interested, you can order.
👉 https://www.mebmarket.com/web/index.php?action=BookDetails&data=YToyOntzOjc6InVzZXJfaWQiO3M6NzoiMTcyNTQ4MyI7czo3OiJib29rX2lkIjtzOjY6IjEwODI0NiI7fQ&fbclid=IwAR11zxJea0OnJy5tbfIlSxo4UQmsemh_8TuBF0ddjJQzzliMFFoFz1AtTo4
.
Personal like the book. You can see this link.
👉 https://www.dropbox.com/s/fg8l38hc0k9b0md/chapter_example.pdf?dl=0
.
Sorry, paper book. I don't have it yet. Sorry.
.
✍ Written by Thai programmer thai progammerTranslated
r predict 在 メンタリスト DaiGo Youtube 的最佳解答
📘この動画内で紹介したおすすめ動画・ニコニコ動画は
知識のNetflix【Dラボ】で見放題!
今なら20日間無料→https://daigovideolab.jp/
🐈
【恐怖と欲望の説得術】歴史を動かした偉人の話し方
【前編】https://www.nicovideo.jp/watch/1589394903
【後編】https://www.nicovideo.jp/watch/1589662563
▶︎本日のオススメ
ファンダム・レボリューション SNS時代の新たな熱狂 を Amazon でチェック! https://amzn.to/35VgPUh
ファスト&スローを Amazon でチェック! https://amzn.to/3ayKWSp
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プロパガンダ:広告・政治宣伝のからくりを見抜く を Amazon でチェック! https://amzn.to/2WsgAx9
メディアとプロパガンダ を Amazon でチェック! https://amzn.to/3dy5Wum
★本日の無料
DaiGoのオーディオブックがAmazonで無料で聞けます。詳しくは↓
▶︎後悔しない超選択術
https://amzn.to/346QeTv
▶︎知識を操る超読書術
https://amzn.to/39AZpfT
▶︎自分を操る超集中力
https://amzn.to/2w7RpFw
▶︎人を操る禁断の文章術
https://amzn.to/2yrHn2N
など、他多数の著書が、Audible30日間無料体験にて1冊無料
Morris, Michael, et al. (2002) Schmooze or lose: Social friction and lubrication in e-mail negotiations.
Cheng, Joey T et al. (2016)Listen, follow me: Dynamic vocal signals of dominance predict emergent social rank in humans.
Stephen M. Smith et al. (1991) Celerity and Cajolery: Rapid Speech May Promote or Inhibit Persuasion through its Impact on Message Elaboration
Jerry M. Burger et al. (2001) The Effect of Fleeting Attraction on Compliance to Requests
Cory R. Scherer et al. (2005) Indecent influence: The positive effects of obscenity on persuasion
Adam M. Grant, et al. (2015) Busy brains, boasters' gains: Self-promotion effectiveness depends on audiences cognitive resources
Nora A. Murphy et al. (2015) Appearing Smart: The Impression Management of Intelligence, Person Perception Accuracy, and Behavior in Social Interaction
Weaver, Kimberlee,Garcia, Stephen M.,Schwarz, Norbert,Miller, Dale T.(2007) Inferring the popularity of an opinion from its familiarity: A repetitive voice can sound like a chorus.
Daniel J. O’Keefe. et al. (2008) Do Loss-Framed Persuasive Messages Engender Greater Message Processing Than Do Gain-Framed Messages? A Meta-Analytic Review
Aiwa Shirako, et al. (2015) Is there a place for sympathy in negotiation? Finding strength in weakness
Kumkale, G. et al. (2004)The Sleeper Effect in Persuasion: A Meta-Analytic Review.
Adam Grant(2014)How I Overcame the Fear of Public Speaking
advantages of being unpredictable: How emotional inconsistency extracts concessions in negotiation
Dariusz DolinskiaRichard Nawratb et al. (1998) Fear-Then-Relief” Procedure for Producing Compliance: Beware When the Danger Is Over
Franklin J. Boster et al. (2009) Dump-and-Chase: The Effectiveness of Persistence as a Sequential Request Compliance-Gaining Strategy
Boaz Hameiri, et al. (2014) Paradoxical thinking as a new avenue of intervention to promote peace
Chenhao Tan et al. (2016) Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions
※この動画は、上記の参考資料および、動画を元に考察したもので、あくまで一説であり、真偽を確定するものではありません。リサーチ協力の鈴木祐さんの論文解説チャンネルもオススメです→http://ch.nicovideo.jp/paleo #今なら
#Dラボとオーディオブックが概要欄から無料
r predict 在 メンタリスト DaiGo Youtube 的最佳貼文
📘この動画内で紹介したおすすめ動画・ニコニコ動画は
知識のNetflix【Dラボ】で見放題!
今なら20日間無料→https://daigovideolab.jp/
🐈
【恐怖と欲望の説得術】歴史を動かした偉人の話し方
【前編】https://www.nicovideo.jp/watch/1589394903
【後編】https://www.nicovideo.jp/watch/1589662563
▶︎本日のオススメ
ファンダム・レボリューション SNS時代の新たな熱狂 を Amazon でチェック! https://amzn.to/35VgPUh
ファスト&スローを Amazon でチェック! https://amzn.to/3ayKWSp
事実はなぜ人の意見を変えられないのか を Amazon でチェック! https://amzn.to/35WD6RN
信頼はなぜ裏切られるのか を Amazon でチェック! https://amzn.to/3cra672
戦争プロパガンダ10の法則 を Amazon でチェック! https://amzn.to/2xYbvD7
プロパガンダ:広告・政治宣伝のからくりを見抜く を Amazon でチェック! https://amzn.to/2WsgAx9
メディアとプロパガンダ を Amazon でチェック! https://amzn.to/3dy5Wum
★本日の無料
DaiGoのオーディオブックがAmazonで無料で聞けます。詳しくは↓
▶︎後悔しない超選択術
https://amzn.to/346QeTv
▶︎知識を操る超読書術
https://amzn.to/39AZpfT
▶︎自分を操る超集中力
https://amzn.to/2w7RpFw
▶︎人を操る禁断の文章術
https://amzn.to/2yrHn2N
など、他多数の著書が、Audible30日間無料体験にて1冊無料
Morris, Michael, et al. (2002) Schmooze or lose: Social friction and lubrication in e-mail negotiations.
Cheng, Joey T et al. (2016)Listen, follow me: Dynamic vocal signals of dominance predict emergent social rank in humans.
Stephen M. Smith et al. (1991) Celerity and Cajolery: Rapid Speech May Promote or Inhibit Persuasion through its Impact on Message Elaboration
Jerry M. Burger et al. (2001) The Effect of Fleeting Attraction on Compliance to Requests
Cory R. Scherer et al. (2005) Indecent influence: The positive effects of obscenity on persuasion
Adam M. Grant, et al. (2015) Busy brains, boasters' gains: Self-promotion effectiveness depends on audiences cognitive resources
Nora A. Murphy et al. (2015) Appearing Smart: The Impression Management of Intelligence, Person Perception Accuracy, and Behavior in Social Interaction
Weaver, Kimberlee,Garcia, Stephen M.,Schwarz, Norbert,Miller, Dale T.(2007) Inferring the popularity of an opinion from its familiarity: A repetitive voice can sound like a chorus.
Daniel J. O’Keefe. et al. (2008) Do Loss-Framed Persuasive Messages Engender Greater Message Processing Than Do Gain-Framed Messages? A Meta-Analytic Review
Aiwa Shirako, et al. (2015) Is there a place for sympathy in negotiation? Finding strength in weakness
Kumkale, G. et al. (2004)The Sleeper Effect in Persuasion: A Meta-Analytic Review.
Adam Grant(2014)How I Overcame the Fear of Public Speaking
advantages of being unpredictable: How emotional inconsistency extracts concessions in negotiation
Dariusz DolinskiaRichard Nawratb et al. (1998) Fear-Then-Relief” Procedure for Producing Compliance: Beware When the Danger Is Over
Franklin J. Boster et al. (2009) Dump-and-Chase: The Effectiveness of Persistence as a Sequential Request Compliance-Gaining Strategy
Boaz Hameiri, et al. (2014) Paradoxical thinking as a new avenue of intervention to promote peace
Chenhao Tan et al. (2016) Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions
※この動画は、上記の参考資料および、動画を元に考察したもので、あくまで一説であり、真偽を確定するものではありません。リサーチ協力の鈴木祐さんの論文解説チャンネルもオススメです→http://ch.nicovideo.jp/paleo #今なら
#Dラボとオーディオブックが概要欄から無料
r predict 在 Amaz Youtube 的精選貼文
Just like a Coldlight Oracle right?
-- Watch live at http://www.twitch.tv/amazhs
-- Check out G2A.com for games at great prices! : http://g2a.com/r/amaz4
Spoiler Alert:
I won. -- Watch live at http://www.twitch.tv/amazhs
r predict 在 Using lmGC(), predict() and plot() 的推薦與評價
the correlation coefficient r. We need to look at a scatter plot to be really sure about it (for plots, see below), but at this point the value ... ... <看更多>
r predict 在 R Tutorial: Predicting once you fit a model - YouTube 的推薦與評價
... <看更多>