• 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.

*** Bestes IPTV *** bester Preis *** gratis Test ***



Data Science Bundle - 180 Hands-On Projects - Course 1 of 3

Tutorials

MyBoerse.bz Pro Member
1ca0520ef6f5eddcc63e039210ff0663.jpeg

Free Download Data Science Bundle - 180 Hands-On Projects - Course 1 of 3
Last updated 10/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 73h 23m | Size: 38.3 GB
Build & Deploy 180 Projects - Data Science, Machine Learning, Deep Learning (Python, Flask, Django, AWS, Azure Cloud)

What you'll learn
Master the essentials of Machine Learning using Python, the go-to language for Data Science.
Learn to build robust Machine Learning models that can withstand real-world uncertainties.
Acquire the skills needed to deploy Machine Learning models, making them functional in a live environment.
Develop a strong intuition for choosing the right Machine Learning models for different tasks.
Implement popular Machine Learning algorithms from scratch, providing you with a deep understanding of their functionalities.
Use SciKit-Learn, the Python library for Machine Learning, to efficiently complete various tasks.
Explore Matplotlib, the Python plotting library, to visualize your data effectively.
Get exposure to Deep Learning, Transfer Learning, and Neural Networks, expanding your skill set.
Requirements
Basic knowledge of data science
Description
Unleash your data science mastery in this dynamic course! Learn to build and deploy machine learning, AI, NLP models, and more using Python and web frameworks like Flask and Django. Elevate your projects to the cloud with Heroku, AWS, Azure, GCP, IBM Watson, and Streamlit. Get ready to turn data into powerful solutions!
Embark on a dynamic learning experience with our comprehensive course, "Applied Data Science: From Theory to Real-World Impact." Dive deep into the world of practical machine learning and data-driven projects, where you'll gain the skills to transform theoretical concepts into tangible solutions.
This hands-on program empowers you to tackle complex problems using cutting-edge techniques, guiding you through the entire project lifecycle. From the inception of ideas to data collection, preprocessing, modeling, and deployment, you'll navigate every stage, honing your skills in real-world settings.
Develop proficiency in deploying models across diverse environments, from interactive web applications to critical business systems. Gain insights into the challenges of model deployment and learn to address them effectively. With a strong emphasis on experiential learning, you'll work on actual industry-inspired projects, implementing strategies that yield measurable results.
"Data-Driven Projects" goes beyond the technical aspects, highlighting the integration of data-driven decision-making into various business landscapes. Witness the fusion of data analytics and strategic thinking, driving business impact through informed insights. Whether you're a seasoned data practitioner or a newcomer, this course equips you with the knowledge and confidence to excel in real-world scenarios.
Elevate your data science journey today and become a proficient problem solver, capable of leveraging data for transformative outcomes that make a difference in today's data-rich world.
In This Course, We Are Going To Work On 60 Real World Projects Listed Below
Project-1: Forecasting Renewable Energy Generation: Time Series and Regression Analysis
Project-2: Predicting Diamond Sales Price with Multiple Regression Methods
Project-3: Ethereum Price Prediction using GRU/LSTMs for Forecasting
Project-4: Detecting Stress Levels from PPG Sensor Data using Neural Networks
Project-5: Classification of Brain Tumors with CNN and OpenCV
Project-6: Age and Gender Prediction from Chest X-Ray Scans using CNN and OpenCV
Project-7: COVID-19 Detection from CT Scans using ResNet, DenseNet, and VGG Models
Project-8: Detecting DeepFakes with ResNet and CNN
Project-9: Automatic Number Plate Recognition using ResNet and CNN
Project-10: Land Segmentation using U-Net Architecture
Project-11: LingoLinx: Unleashing Multilingual Magic - Language Translator App on Heroku
Project-12: AdView Pro: Cracking the Code of Ad View Predictions with IBM Watson on Heroku
Project-13: LappyPricer: Decoding Laptop Prices with Heroku's Predictive Powers
Project-14: TextWise: Unveiling Insights from WhatsApp Text with Heroku's Analytical Arsenal
Project-15: SmartCourse: Guiding Your Academic Journey - Course Recommendation System on Heroku
Project-16: IPL Prophets: Predicting IPL Match Wins with a Touch of Heroku Magic
Project-17: BodyFit: Sculpting Your Body Fat Estimator App on Microsoft Azure
Project-18: CareerPath: Paving the Way to Campus Placement Success on Microsoft Azure
Project-19: AutoCar: Driving the Future of Car Acceptability Prediction on Google Cloud
Project-20: GenreGenius: A Journey into Book Genres with Amazon Web Services
Project-21: DNA Seeker: Unraveling Genetic Clues - E.Coli Classification Adventure on AWS
Project-22: WordWizard: Unleashing Sentence Sorcery - Predicting the Next Word on AWS
Project-23: SeqMaster: Journey into Sequence Prediction - LSTM Adventures on AWS
Project-24: KeywordGenie: Unlocking Textual Treasures - Keyword Extraction using NLP on Azure
Project-25: SpellCheck Plus: Vanishing Typos - Spelling Correction Wizardry on Azure
Project-26: MusicTrends: Dancing with Popularity - Music Popularity Classification on Google App Engine
Project-27: AdClassify: Decoding Advertisements - Advertisement Classification on Google App Engine
Project-28: DigitDetect: Cracking the Code of Image Digits - Image Digit Classification on AWS
Project-29: EmoSense: Delving into Emotions - Emotion Recognition with Neural Networks on AWS
Project-30: CancerGuard: Fighting Against Breast Cancer - Breast Cancer Classification on AWS
Project-31: Unsupervised Clustering of COVID Nucleotide Sequences using K-Means
Project-32: Weed Detection in Soybean Crops using Computer Vision
Project-33: PixelPal: Transforming Images with OpenCV and Tkinter - Image Editor Application
Project-34: BrandQuest: Unveiling Brand Identifications with Tkinter and SQLite - Brand Identification Game
Project-35: TransactionTracker: Monitoring Financial Flows with Tkinter and SQLite - Transaction Application
Project-36: LearnEase: Nurturing Knowledge with Django - Learning Management System
Project-37: NewsWave: Riding the Waves of News - Create A News Portal with Django
Project-38: StudentVerse: Journey into Student Life - Create A Student Portal with Django
Project-39: ProductivityPro: Tracking Progress with Django and Plotly - Productivity Tracker
Project-40: StudyConnect: Forging Study Bonds - Create A Study Group with Django
Power BI Projects
Project-41: Global Data Professionals Benchmarking Dashboard
Project-42: Beijing Air Quality Dashboard: DAX and Visualizations
Project-43: Real Estate in Daegu: Apartment Pros and Cons Analysis
Project-44: Super Market Sales Analysis: Power Query and DAX
Project-45: COVID-19 WHO Dataset Insights: Power Query and DAX
Project-46: Credit Card Defaulters Analysis: Power Query and DAX
Project-47: Crime in Chicago: 3-Year Analysis with Visualization
Project-48: Customer Churn Analysis: Real-World Business Problem
Project-49: Customer Churn Analysis (Advanced Features): Data Modeling
Project-50: Attrition Analysis: HR Data Transformation and Visualization
Tableau Projects
Project-51: Revenue Analysis Dashboard: Business Insights and Trends
Project-52: AirBnbs in Seattle: Rental Market Analysis
Project-53: New Year Resolution Tweets: Social Media Analysis
Project-54: Road Accident in the UK: Safety Analysis
Project-55: Ecommerce Sales Dashboard: Sales Optimization
Project-56: Super Store Sales Dashboard: Retail Analysis
Project-57: Credit Card Complaints: Customer Feedback Analysis
Project-58: Data Science Career Dashboard: Job Market Trends
Project-59: Amazon Prime Video Dashboard: Streaming Insights
Project-60: Traffic Collision in Seattle: Safety and Traffic Analysis
Tip: Create A 60 Days Study Plan , Spend 1-3hrs Per Day, Build 60 Projects In 60 Days.
The Only Course You Need To Become A Data Scientist, Get Hired And Start A New Career
Note: This Course Is Worth Of Your Time And Money, Enroll Now Before Offer Expires.
Who this course is for
Beginners in data science
Homepage



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