• Regeln für den Audio-Bereich:

    Allgemeine Boardregeln: MyBoerse-bz-Regelwerk Regelwerk Audioboerse

    1. Das richtige Forum

    Wähle ein passendes Unterforum für dein Angebot

    2. Doppelte Threads vermeiden / Ein Thread pro Interpret


    Da es hier langsam ausartet mit gleichen Interpreten, aber verschiedenen Jahren, gilt ab sofort: Nur noch ein Thread pro Interpret, unabhängig von der Jahreszahl der verschiedenen Alben. Wünschenswert wäre es wenn ihr den Titel ab sofort so benennt: Interpret - Diskographie

    Um Doppelpost zu vermeiden, nutze vor dem Posten die Suchenfunktion. Gibt es schon einen passenden Thread, dann poste Dein Angebot dort hinein. Für einzelne Alben einer Sammlung bzw. Hörbuchreihen bitte in den passenden Sammelthreads posten.

    3. Der richtige Titel

    Gib dem Thread einen einfachen aber vernünftigen Titel, der zum Angebot passt. Um den Thread besser über die Suche zu finden, solltest du einen normalen Titel benutzen. Bei Threads in den Foren Musik, HQ Audio / Lossless und Soundtracks / OST immer das Jahr am Ende des Threadtitels in Klammern angeben, z.B.: Interpretname - Albumname (2016)

    4. Die richtigen Angaben

    Ein Thread/Thema in der Audio-Börse muss dem User Informationen über das Angebot geben können.

    Pflichtangaben:

    Bild des Uploads
    Genre
    Bitrate der Musik Datei: in Kbit/s
    Hoster
    Größe in MB oder GB
    Tracklist

    Optional: Angabe wenn Cover dabei sind.


    Sollte ein Angebot diese Pflichtangaben nicht beinhalten, wird der Verfasser darauf hingewiesen. Sollte dieses dann nicht geändert werden, werden die Beiträge gelöscht.

    (Sollte der Upload nicht als mp3 vorliegen, sondern als ogg/Bin/Cue o.Ä., dann ist dies auch eine Pflichtangabe)

    5. Defekte/nicht verfügbare Links und andere Probleme mit einem Upload

    Sollte ein Upload down sein, dann meldet es per PN dem Uploader. Gibt es zwei Threads zum gleichen Thema oder ein Upload im falschen Forum, dann meldet dies via "Beitrag melden" Funktion, diese befindet sich neben dem Bedanken-Button.

    6. Reupp- /Hosteranfragen
    Reuppanfragen oder auch Anfragen ob es bei einem anderen Hoster geuppt werden kann, bitte direkt per PN an den Uploader und nicht in den Thread.
  • Bitte registriere dich zunächst um Beiträge zu verfassen und externe Links aufzurufen.




Flutter and Linear Regression - Build Prediction Apps Flutter

Tutorials

MyBoerse.bz Pro Member
d1b35243ed44a9911cd79e69b00c4367.jpeg

Free Download Flutter and Linear Regression - Build Prediction Apps Flutter
Published 11/2023
Created by Hamza Asif
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 62 Lectures ( 4h 47m ) | Size: 3.26 GB

Train regression models for Flutter | Use regression models in Flutter | Tensorflow Lite models integration in Flutter
What you'll learn
Train regression models for Mobile Applications
Integrate regression models in Flutter for both Android & IOS
Use of Tensorflow Lite models in Flutter
Train Any Prediction Model & use it in Flutter Applications
Data Collection & Preprocessing for model training
Basics of Machine Learning & Deep Learning
Understand the working of artificial neural networks for model training
Basic syntax of python programming language
Use of data science libraries like numpy, pandas and matplotlib
Analysing & using advance regression models in Flutter Applications
Requirements
Android studio & Flutter installed in your PC
Description
Welcome to the exciting world of Flutter and Linear Regression! I'm Muhammad Hamza Asif, and in this course, we'll embark on a journey to combine the power of predictive modeling with the flexibility of Flutter app development. Whether you're a seasoned Flutter developer or new to the scene, this course has something valuable to offer you.Course Overview: We'll begin by exploring the basics of Machine Learning and its various types, and then delve into the world of deep learning and artificial neural networks, which will serve as the foundation for training our regression models in Flutter.The Flutter-ML Fusion: After grasping the core concepts, we'll bridge the gap between Flutter and Machine Learning. To do this, we'll kickstart our journey with Python programming, a versatile language that will pave the way for our regression model training.Unlocking Data's Power: To prepare and analyze our datasets effectively, we'll dive into essential data science libraries like NumPy, Pandas, and Matplotlib. These powerful tools will equip you to harness data's potential for accurate predictions.Tensorflow for Mobile: Next, we'll immerse ourselves in the world of TensorFlow, a library that not only supports model training using neural networks but also caters to mobile devices, including Flutter.Course Highlights:Training Your First Regression Model:Harness TensorFlow and Python to create a simple regression model.Convert the model into TFLite format, making it compatible with Flutter.Learn to integrate the regression model into Flutter apps for Android and iOS.Fuel Efficiency Prediction:Apply your knowledge to a real-world problem by predicting automobile fuel efficiency.Seamlessly integrate the model into a Flutter app for an intuitive fuel efficiency prediction experience.House Price Prediction in Flutter:Master the art of training regression models on substantial datasets.Utilize the trained model within your Flutter app to predict house prices confidently.The Flutter Advantage: By the end of this course, you'll be equipped to:Train advanced regression models for accurate predictions.Seamlessly integrate regression models into your Flutter applications.Analyze and use existing regression models effectively within the Flutter ecosystem.Who Should Enroll:Aspiring Flutter developers eager to add predictive modeling to their skillset.Enthusiasts seeking to bridge the gap between Machine Learning and mobile app development.Data aficionados interested in harnessing the potential of data for real-world applications.Step into the World of Flutter and Predictive Modeling: Join us on this exciting journey and unlock the potential of Flutter and Linear Regression. By the end of the course, you'll be ready to develop Flutter applications that not only look great but also make informed, data-driven decisions.Enroll now and embrace the fusion of Flutter and predictive modeling!
Who this course is for
Beginner Flutter Developer who want to build Machine Learning based Flutter Applications
Aspiring Flutter developers eager to add predictive modeling to their skillset
Enthusiasts seeking to bridge the gap between Machine Learning and mobile app development.
Machine Learning Engineers looking to build real world applications with Machine Learning Models
Homepage








Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live
No Password - Links are Interchangeable
d1b35243ed44a9911cd79e69b00c4367.jpeg

Flutter and Linear Regression - Build Prediction Apps Flutter
Published 11/2023
Created by Hamza Asif
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 62 Lectures ( 4h 47m ) | Size: 3.26 GB

Train regression models for Flutter | Use regression models in Flutter | Tensorflow Lite models integration in Flutter
What you'll learn
Train regression models for Mobile Applications
Integrate regression models in Flutter for both Android & IOS
Use of Tensorflow Lite models in Flutter
Train Any Prediction Model & use it in Flutter Applications
Data Collection & Preprocessing for model training
Basics of Machine Learning & Deep Learning
Understand the working of artificial neural networks for model training
Basic syntax of python programming language
Use of data science libraries like numpy, pandas and matplotlib
Analysing & using advance regression models in Flutter Applications
Requirements
Android studio & Flutter installed in your PC
Description
Welcome to the exciting world of Flutter and Linear Regression! I'm Muhammad Hamza Asif, and in this course, we'll embark on a journey to combine the power of predictive modeling with the flexibility of Flutter app development. Whether you're a seasoned Flutter developer or new to the scene, this course has something valuable to offer you.Course Overview: We'll begin by exploring the basics of Machine Learning and its various types, and then delve into the world of deep learning and artificial neural networks, which will serve as the foundation for training our regression models in Flutter.The Flutter-ML Fusion: After grasping the core concepts, we'll bridge the gap between Flutter and Machine Learning. To do this, we'll kickstart our journey with Python programming, a versatile language that will pave the way for our regression model training.Unlocking Data's Power: To prepare and analyze our datasets effectively, we'll dive into essential data science libraries like NumPy, Pandas, and Matplotlib. These powerful tools will equip you to harness data's potential for accurate predictions.Tensorflow for Mobile: Next, we'll immerse ourselves in the world of TensorFlow, a library that not only supports model training using neural networks but also caters to mobile devices, including Flutter.Course Highlights:Training Your First Regression Model:Harness TensorFlow and Python to create a simple regression model.Convert the model into TFLite format, making it compatible with Flutter.Learn to integrate the regression model into Flutter apps for Android and iOS.Fuel Efficiency Prediction:Apply your knowledge to a real-world problem by predicting automobile fuel efficiency.Seamlessly integrate the model into a Flutter app for an intuitive fuel efficiency prediction experience.House Price Prediction in Flutter:Master the art of training regression models on substantial datasets.Utilize the trained model within your Flutter app to predict house prices confidently.The Flutter Advantage: By the end of this course, you'll be equipped to:Train advanced regression models for accurate predictions.Seamlessly integrate regression models into your Flutter applications.Analyze and use existing regression models effectively within the Flutter ecosystem.Who Should Enroll:Aspiring Flutter developers eager to add predictive modeling to their skillset.Enthusiasts seeking to bridge the gap between Machine Learning and mobile app development.Data aficionados interested in harnessing the potential of data for real-world applications.Step into the World of Flutter and Predictive Modeling: Join us on this exciting journey and unlock the potential of Flutter and Linear Regression. By the end of the course, you'll be ready to develop Flutter applications that not only look great but also make informed, data-driven decisions.Enroll now and embrace the fusion of Flutter and predictive modeling!
Who this course is for
Beginner Flutter Developer who want to build Machine Learning based Flutter Applications
Aspiring Flutter developers eager to add predictive modeling to their skillset
Enthusiasts seeking to bridge the gap between Machine Learning and mobile app development.
Machine Learning Engineers looking to build real world applications with Machine Learning Models
Homepage








Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live
No Password - Links are Interchangeable
 
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