Tensorflow による機械学習 | Python レベル 5
この機械学習コースでは、TensorFlow、線形回帰、ニューラルネットワーク、モデルチューニングなどの基本的な概念を実践的なプロジェクトを通じて学びます。学生はデータセットを使用してスキルを適用し、独自の最終的な機械学習プロジェクトを作成します。
AI Code Academy
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含まれるもの
10 ライブミーティング
10 授業時間プロジェクト
週あたり 2-4 時間. Projects are not mandatory but we strongly encourage students to complete them.テスト
含まれるこの文章は自動翻訳されています
このクラスで学べること
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.
学習到達目標
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.
シラバス
10 レッスン
10 週間以上レッスン 1:
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 60 分のオンラインライブレッスン
レッスン 2:
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. 60 分のオンラインライブレッスン
レッスン 3:
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 60 分のオンラインライブレッスン
レッスン 4:
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 60 分のオンラインライブレッスン
その他の情報
外部リソース
学習者は、Outschoolが提供する基本ツール以外のアプリやウェブサイトを使用する必要はありません。
参加しました April, 2020
4.7
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教師の専門知識と資格
**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.レビュー
ライブグループコース
$27
毎週または$269 10 クラス分週に1回、 10 週間
60 分
8 人がクラスを受けました
オンラインライブ授業
年齢: 13-18
クラス人数： 4 人-8 人
