Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Microsoft ML.NET
Search
Sponsored
·
Ship Features Fearlessly
Turn features on and off without deploys. Used by thousands of Ruby developers.
→
Cihan Yakar
February 19, 2019
Programming
0
510
Microsoft ML.NET
ML.NET 0.10 sürümü ile bir sınıflandırma örneği anlatılmıştır.
Cihan Yakar
February 19, 2019
Tweet
Share
More Decks by Cihan Yakar
See All by Cihan Yakar
Auto ML
cihanyakar
0
750
Microsoft Azure Machine Learning Studio
cihanyakar
0
1.3k
IntelliCode
cihanyakar
0
490
Microsoft ML.net ile Segmentasyon Çalışması
cihanyakar
0
530
Xamarin ❤ ML.net
cihanyakar
1
590
.NET CORE 2.2 & .NET CORE 3.
cihanyakar
0
680
Visual Studio 2019
cihanyakar
0
610
Geldiğim Nokta: XAMARIN & OYUN
cihanyakar
0
87
Visual Studio ve Takım Çalışması
cihanyakar
0
370
Other Decks in Programming
See All in Programming
16年目のピクシブ百科事典を支える最新の技術基盤 / The Modern Tech Stack Powering Pixiv Encyclopedia in its 16th Year
ahuglajbclajep
5
1k
Data-Centric Kaggle
isax1015
2
770
CSC307 Lecture 09
javiergs
PRO
1
830
余白を設計しフロントエンド開発を 加速させる
tsukuha
7
2.1k
AI & Enginnering
codelynx
0
110
生成AIを使ったコードレビューで定性的に品質カバー
chiilog
1
260
20260127_試行錯誤の結晶を1冊に。著者が解説 先輩データサイエンティストからの指南書 / author's_commentary_ds_instructions_guide
nash_efp
1
960
Oxlint JS plugins
kazupon
1
890
15年続くIoTサービスのSREエンジニアが挑む分散トレーシング導入
melonps
2
190
ThorVG Viewer In VS Code
nors
0
770
Patterns of Patterns
denyspoltorak
0
1.4k
Fragmented Architectures
denyspoltorak
0
150
Featured
See All Featured
Efficient Content Optimization with Google Search Console & Apps Script
katarinadahlin
PRO
0
320
Responsive Adventures: Dirty Tricks From The Dark Corners of Front-End
smashingmag
254
22k
Claude Code のすすめ
schroneko
67
210k
Noah Learner - AI + Me: how we built a GSC Bulk Export data pipeline
techseoconnect
PRO
0
110
Reflections from 52 weeks, 52 projects
jeffersonlam
356
21k
Winning Ecommerce Organic Search in an AI Era - #searchnstuff2025
aleyda
0
1.9k
Darren the Foodie - Storyboard
khoart
PRO
2
2.4k
The Success of Rails: Ensuring Growth for the Next 100 Years
eileencodes
47
7.9k
Building an army of robots
kneath
306
46k
Pawsitive SEO: Lessons from My Dog (and Many Mistakes) on Thriving as a Consultant in the Age of AI
davidcarrasco
0
64
Mobile First: as difficult as doing things right
swwweet
225
10k
The World Runs on Bad Software
bkeepers
PRO
72
12k
Transcript
MICROSOFT ML.NET Cihan YAKAR
[email protected]
MAKINE ÖĞRENMESI public static int PredictQuality(Wine wine) { return (int)(wine.CitricAcid
* 0.7 + wine.Alcohol * 0.2 + wine.CitricAcid * 0.5); }
MAKINE ÖĞRENMESI public static int PredictQuality(Wine wine) { return ***
ML *** }
MAKINE ÖĞRENMESI
SINIFLANDIRMA public static Hayvan HangiHayvan(Picture x) { return Hayvan.Kurbaga; }
DEMETLEME / KÜMELEME public static Hayvan[][] Demetle(Hayvan[] hayvanat, int num)
{ }
REGRESYON public static float Sicaklik(DateTime tarih) { return 45; }
İLK DEĞİL • Machine Learning Server 9.3, • Azure Machine
Learning Service, • Azure Machine Learning Studio, • Azure Databricks (Spark-based analytics platform), • SQL Server Machine Learning Services, • Azure Cognitive Service, • Azure Data Science Virtual Machine, • Windows ML.
ML.NET Load Data IDataView Transform Data ITransformer Choose Algorithm IEstimator
Train Model Evaluate Model PredictionEngine Deploy Model
DEMO – VERİYİ İNCELEYELİM
DEMO – VERİYİ İNCELEYELİM
DEMO – VERİYİ İNCELEYELİM
DEMO – VERİYİ İNCELEYELİM
DEMO – VERİYİ İNCELEYELİM 0 100 200 300 400 500
600 700 800 3 4 5 6 7 8 Kalitelerin Dağılımı
DEMO – VERİYİ İNCELEYELİM 0 100 200 300 400 500
600 700 800 3 4 5 6 7 8 Kalitelerin Dağılımı
DEMO – KODA GEÇELİM
TEŞEKKÜRLER WWW.TEKNOLOT.COM