여름 캠프: Tensorflow를 사용한 머신 러닝 알고리즘(Python 레벨 5)
이 과정에서는 학생들에게 TensorFlow를 가르치고 머신 러닝 프로젝트를 만드는 기능을 배우고, 모델과 모델이 저지르는 오류를 분석하여 모델을 반복하고 개선하는 방법을 배웁니다. Python 코딩 기술과 경험이 필요합니다.
AI Code Academy
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4.7
수강 후기 수:(1,743)
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10개의 라이브 미팅
수업 12 시간 30 분 시간프로젝트
주당 2-4시간. Projects are not mandatory but we strongly encourage students to complete them.학습 평가
포함됨보고계신 지문은 자동 번역 되었습니다
수업 소개
This comprehensive Machine Learning Fundamentals course covers essential concepts and practical applications across ten structured lessons. Beginning with an introduction to TensorFlow and basic machine learning principles, students progress through topics such as linear regression, model tuning strategies, K-NN clustering, decision forests, and neural networks, including feed-forward networks and convolutional neural networks (CNNs). Each lesson incorporates hands-on projects using datasets like MNIST and CIFAR10, where students implement algorithms, tune models for optimal performance, and visualize results. The course culminates in a final project phase where participants develop and present their own machine learning applications, exploring diverse topics from image classification to model ensembling and hyperparameter optimization. For a week to week program, check out the syllabus.
학습 목표
This Machine Learning Fundamentals course covers TensorFlow introduction, basic principles, linear regression, model tuning, K-NN clustering, decision forests, and neural networks like CNNs.Through hands-on projects with MNIST and CIFAR10 datasets, students implement algorithms, optimize models, and present final projects on topics including image classification and hyperparameter optimization.
강의 계획서
10 레슨
2 주 이상레슨1:
Intro To TensorFlow
Objectives:
Learn the basics of machine learning
What is learning?
History of machine learning
Regression vs classification
Introduce TensorFlow
Installing TensorFlow
What is a Tensor?
Low-level API and high-level API
How do Tensors perform computations?
Tensorflow variables
Project 1: Perform basic computations with TensorFlow
Matrix addition, matrix multiplication using tensors in TensorFlow 75 분 온라인 라이브 레슨
레슨2:
Linear Regression
This project aims to teach linear regression fundamentals, including hypothesis setup with the equation 𝑦 = 𝑚 𝑥 + 𝑏 y=mx+b, where 𝑚 m represents weights and 𝑏 b denotes biases. Participants will learn to compute these parameters using gradient descent and understand the mean squared error cost function. Using TensorFlow and NumPy, they will implement a linear regression model, iteratively refining weights and biases over multiple epochs and visualizing model performance. 75 분 온라인 라이브 레슨
레슨3:
Model Tuning
Objectives
Why do we need to tune models?
Convergence problems
Preparation
Strategies for tuning models
Grid Search
Random Search
Data transformation
Project 3: Tune the linear regression model to produce better results
Implement Grid Search
Implement Random Search
Implement a data transformation 75 분 온라인 라이브 레슨
레슨4:
K-NN Clustering
Objectives:
How do we solve classification problems?
Problems with classification
Strategies and models to use
K-NN Algorithms
How do clustering algorithms work?
How does the K-NN algorithm perform classification
How do we measure distance?
What is the effect of the K hyperparameter?
Project 4: MNIST Classification with K-NN
Import the dataset and process it
Implement the K-NN algorithm
Visualize the results
Tune the model for better results 75 분 온라인 라이브 레슨
그 외 세부 사항
Outschool 외 필요 앱/웹사이트
아웃스쿨 사이트의 기능 외 별도의 앱이나 웹 사이트를 사용할 필요가 없습니다.
가입일: April, 2020
4.7
1743수강 후기
인기 수업
교사 전문성 및 자격증
**USE PROMO CODE: CODEAIPROMO10 FOR $10 OFF ANY COURSE - Valid until Nov, 25 **
~We offer early registration, sibling discounts, and multi-course bundles. ~
~Check out our complete Outschool offering here: https://shorturl.at/bcBGP ~
At AI Code Academy, we specialize in project-based STEM coding, AI, and mathematics programs for young learners. We are one of the few organizations that offer AI and machine learning courses tailored for kids. Our comprehensive curriculum spans from basic computer skills and Scratch coding to more advanced Python, Java, web design, game development, and AI machine learning projects.
Our unique focus is on introducing students to AI early, helping them grasp complex concepts like machine learning, data analysis, and smart devices, while also reinforcing mathematics skills, essential for their success in STEM fields.
With a team of passionate instructors—college students and recent graduates with degrees in Engineering and Computer Science—we provide hands-on, real-world projects that prepare students for future careers in AI, coding, robotics, and mathematics.리뷰
실시간 그룹 수업
10 회 수업에
US$259
2주 동안 주당 5회
75분
1 명의 학생이 수업을 완료함
실시간 화상 수업
연령: 13-18
수업당 학습자 4-8 명
