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Deep Learning & Machine Learning

Keras, the complete conquest of the common language of artificial intelligence

This is a comprehensive course on Keras theory and practice that uses Keras and Python, the common language of artificial intelligence, to learn various useful machine learning regression, classification, and deep learning neural network projects along with theory.

(3.2) 12 reviews

203 learners

  • nomad
Tensorflow
Machine Learning(ML)
Deep Learning(DL)
Keras

Reviews from Early Learners

What you will learn!

  • Understanding and Using Keras

  • Machine learning, deep learning model creation

  • Problem Solving with Keras

  • Predicting machine learning classification results

  • Predicting machine learning regression results

  • Understanding artificial intelligence, machine learning, and deep learning

  • Data processing for machine learning and deep learning

  • Data Analysis Using Python

  • Integrating Keras and TensorFlow

Keras, the undisputed lingua franca of artificial intelligence

Keras, a Python-based machine learning and deep learning library, is gaining traction as the lingua franca of artificial intelligence. It has gained widespread popularity, particularly since TensorFlow 2.0 adopted it as an official high-level language. This course covers everything essential to learning AI, machine learning, and deep learning, from basic Keras knowledge to practical project skills and advanced techniques.

Using Keras and Python, the common language of artificial intelligence, we can perform various useful machine learning regression, classification, and

This is a comprehensive course on Keras theory and practice that teaches deep learning neural network projects along with theory.

Getting Started with Keras

Don't know what Keras is or why you should use it? Don't worry. Even if you're new to Keras or AI, we'll explain everything from the very beginning: what Keras is, how it differs from machine learning frameworks like TensorFlow, and how to install it.

Keras Basics

Don't dive headfirst into deep learning just because Keras is optimized for it! Keras and AI aren't subjects you have to memorize. Just as you would do a gentle warm-up before swimming, before using Keras, learn the basic concepts and usage of Keras's architecture, models, layers, summary, compile, and fit.

Four practical projects

We'll build a variety of practical machine learning and deep learning projects using Keras and compare them with TensorFlow code to hone your skills.

Learn the fundamentals of linear regression and use Keras and Python TensorFlow to analyze and predict Boston Marathon data.

Using big data from approximately 80,000 Boston Marathon events, we select a desired runner and machine learning learns their times up to 30km. We then use linear regression to predict the remaining 35, 40, and 42.195km times and compare them with actual data. We learn the concepts and techniques for solving linear regression problems using TensorFlow.

This time, we will learn the basics and solutions to regression problems that take in multiple variables and output multiple outputs.

Using the Multi-Variable Input and Multi-Output Regression technique, machine learning that receives gender, age, and pace values as input and learns from about 80,000 Boston Marathon big data predicts not only the completion record but also the records for each 10, 20, and 30 km section.
Before entering a marathon, enter your gender, age, and pace data to check your predicted time class. Based on past Boston Marathon times, we'll predict your time class.

Using the Multinomial Classification technique of Logistic Regression, we divide the marathon completion records into three grades: 'Outstanding (>25%)', 'Average (25~75%)', and 'Below (<75%)', and predict your expected grade using Keras.
We will carry out a project to recognize handwritten digit images by creating MNIST Digit Recognition using a deep learning neural network.

We will carry out a project step by step to learn and recognize 70,000 handwritten digit images using the Deep Learning Multi-Layer Neural Network technique.

Special lecture

'Model accuracy over 99%  We have added a special lecture titled 'Raising the bar'. This lecture is titled ' [ Raspberry Pi ] IoT Deep Learning Computer Vision Practice'.  The project began with a question from students in the MNIST handwriting model: "Why can't the MNIST handwriting model say '7' is '7'?" While the model's accuracy is a factor, as are the program's exception handling and the raw MNIST data, the existing Nueral Network model was too simple for training purposes, so I reconfigured it to increase its accuracy to 99.38%.

 

Enhancing Keras

We'll teach you a variety of useful advanced techniques for practical use with Keras, including History, EarlyStopping, ModelCheckPoint, and the graphical user interface. Your Keras projects will become even more valuable.

Please look forward to future lectures on deep learning, Tensorflow.js, and more.
The materials and program sources used in the lecture can be found on the website Creapple (www.creapple.com), a knowledge learning platform I run.

Taking courses on Python fundamentals, data visualization/analysis, and machine learning will be of great help in carrying out your project.

Python 100-Minute Core Course
The core and fundamentals of Python
Once you master the skills, it will be a great help in other courses.
Python Data Visualization Analysis Practical Project

Machine learning using Python's Pandas, Matplotlib, and Seaborn,
Data that can be utilized in various projects, including deep learning
Learn visualization and analysis techniques at the same time.

Mastering Python Machine Learning - Marathon Record Prediction Project

Machine learning using Python and Tensorflow
Learn both concepts and practical skills. Five core topics.
We will hone your skills by working on various projects together.

Recommended for
these people

Who is this course right for?

  • Those who want to use artificial intelligence in practice

  • Those who want to develop basic knowledge for machine learning and deep learning

  • Anyone who wants to learn data science

  • Those who want to develop Keras concepts and practical skills at the same time

  • Anyone working on a data analysis project

  • For those preparing for machine learning/deep learning projects

  • For those preparing for TensorFlow 2.0

Need to know before starting?

  • Complete mastery of Python machine learning - Marathon record prediction project

  • Python Data Processing, Visualization - Python Data Visualization Analysis Practical Project

  • Python Basics - Python 100-minute core lecture

  • Willingness to study hard

Hello
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Answers

4.4

Rating

25

Courses

"노마드크리에이터: 당신의 꿈, 우리의 여정"

대한민국과 NVIDIA가 인정한 딥테크, 싱가포르가 선택한 핀테크 스타트업, 글로벌 무대에서 당신의 가능성을 실현합니다.

노마드크리에이터는 개인의 성장을 넘어, 스타트업으로 도약하며 전 세계를 무대로 전문적인 IT 강의를 제공하고 있습니다.
2019년, 싱가포르 정부의 Entrepass Innovator 프로그램을 통해 시작된 우리의 여정은 곧 혁신적인 스타트업의 이야기로 확장되었습니다.
2020년에는 대한민국에서 인공지능 핀테크 솔루션을 개발하며 딥테크 분야의 선두주자로 자리매김했고, NVIDIA 협업 프로그램 최우수 프로젝트ASUS Global Startup Challenge Award를 포함한 다양한 글로벌 인정과 성과를 이뤘습니다.
2023년에는 NVIDIA의 지원으로 미국에 회사를 설립하며 글로벌 시장을 향한 도약을 시작했습니다.

image.png

경험을 넘어, 비전을 공유합니다.

스타트업 창업 이전, LG CNS와 티머니 등에서 25년간 System Engineer, Project Manager, IT Consultant로서 글로벌 프로젝트를 이끌며 실전 경험과 전문성을 쌓았습니다.
PMP, SAP BW, SCJP, MCSE+DBA, OCP-DBA와 같은 전문 자격을 기반으로, 프로그램 개발, 프로젝트 관리, IT 솔루션 설계 등 다양한 분야에서 성공적인 도전을 이어왔습니다.

이제, 노마드크리에이터는 이러한 경험과 노하우를 집약하여 누구나 쉽고 재미있게 배울 수 있는 교육 콘텐츠를 제공합니다. 실무 중심의 강의부터 최신 기술 트렌드를 반영한 전문 과정까지, 개인의 성장을 위한 맞춤형 학습을 제안합니다.

우리의 미션: "꿈을 현실로, 도전을 기회로"

기술과 교육의 융합으로 더 많은 사람들이 자신만의 가능성을 실현하도록 돕습니다.

노마드크리에이터와 함께라면, 당신의 꿈은 더 이상 멀리 있지 않습니다.

지금 이 순간에도 누군가는 새로운 것을 배우고, 더 나은 자신이 되기 위해 노력하고 있습니다.

하지만 정보의 홍수 속에서 필요한 지식을 찾는 데 소중한 시간을 잃는 일이 얼마나 많습니까?

노마드크리에이터는 이 문제를 해결하고자 합니다.

우리는 지식을 창의적으로 엮어내어, 시간을 아끼고, 가치를 극대화하는 경험을 제공합니다. 우리의 목표는 단순한 정보 전달을 넘어, 지식을 작품처럼 아름답게 전달하는 것입니다.

노마드크리에이터와 함께라면, 당신의 배움은 더 쉽고, 빠르며, 가치 있는 결과를 만들어낼 것입니다.

"배움의 여정에 가치를 더하다, 노마드크리에이터."

이것이 우리가 꿈꾸는 미래입니다.

Curriculum

All

25 lectures ∙ (4hr 8min)

Published: 
Last updated: 

Reviews

All

12 reviews

3.2

12 reviews

  • Maketh Manners님의 프로필 이미지
    Maketh Manners

    Reviews 1

    Average Rating 3.0

    3

    64% enrolled

    선수과정을 너무나 자주 언급하시고, 설명이 지나치게 간결한 것 같습니다.

    • wonjun.jung님의 프로필 이미지
      wonjun.jung

      Reviews 6

      Average Rating 5.0

      5

      100% enrolled

      선수 과목을 먼저 들어야 하는 과목입니다. 약간 old 버전으로 강의된 부분도 있고요..(물론 장단점은 있죠..)

      • qpzkdbwm님의 프로필 이미지
        qpzkdbwm

        Reviews 1

        Average Rating 5.0

        5

        100% enrolled

        감사합니다.

        • tylove0930님의 프로필 이미지
          tylove0930

          Reviews 4

          Average Rating 3.8

          4

          100% enrolled

          좋네요ㅎㅎ

          • zepyr님의 프로필 이미지
            zepyr

            Reviews 8

            Average Rating 4.8

            3

            100% enrolled

            선수과목을 완벽히 이해한 상태 또는 선수과목을 들으신 다음 수강하시기를 바랍니다. 저같은 경우 선수과목을 완강했지만 내용을 아직 소화하지 못해 케라스 강의를 따라가기에 좀 버거운면이 있었습니다. 예제의 경우 선수과목의 것들(마라톤)을 사용하기 때문에 선수과목을 듣지 않았을 경우 예제를 이해하기 어려운 부분이 있을것 같습니다.

            $26.40

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