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Machine Learning With Tensorflow | Python Level 5

This Machine Learning course teaches essential concepts like TensorFlow, linear regression, neural networks, and model tuning through hands-on projects. Students apply skills using datasets & create their own final machine learning projects
AI Code Academy
Average rating:
4.7
Number of reviews:
(1,743)
Popular
Class

What's included

10 live meetings
10 in-class hours
Projects
2-4 hours per week. Projects are not mandatory but we strongly encourage students to complete them.
Assessment
included

Class Experience

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.
Learning Goals
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.
learning goal

Syllabus

10 Lessons
over 10 Weeks
Lesson 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 mins online live lesson
Lesson 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 mins online live lesson
Lesson 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 mins online live lesson
Lesson 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 mins online live lesson

Other Details

External Resources
Learners will not need to use any apps or websites beyond the standard Outschool tools.
Joined April, 2020
4.7
1743reviews
Popular
Profile
Teacher expertise and credentials
**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.

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Live Group Course
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$27

weekly or $269 for 10 classes
1x per week, 10 weeks
60 min

Completed by 8 learners
Live video meetings
Ages: 13-18
4-8 learners per class

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