Machine Learning Honors

Machine Learning Honors is an elective class in the pathway, and is the only course of its kind offered in the area.

I really enjoyed collaborating with my peers on solving errors in the labs. I liked the fact that labs allowed me to practice the skills I learned in class, and allowed me to tackle new problems as well.

Sia
University of California, Berkeley

I didn't even know how to code before this but Mr. Dagler opened my eyes.

Andrew
Class of 2025

I really enjoy this class. I like how there is a lot of time to learn and finish assignments. This is one of the few classes I feel like I learned something in. I had a great time.

Jumanah
Class of 2025

MLH repeats all the fun aspects with AP CSA, but now with an emphasis on machine learning. Even if you think CS or math isn't your cup of tea, this class is still appealing because most concepts should feel intuitive, and Python is easy to learn and understand. Plus, this course doesn't have that much homework, or need crazy in-depth knowledge about math, you just need to pay attention and think logically. Anyone can take this class and perform well in it.

Brentt
Class of 2025

I really enjoyed doing projects in MLH because they analyzed real world data like housing prices, purchasing power based on salary and age, and energy efficiency. Our projects teach us important ML topics like regression and classification.

Gaby
Class of 2025

Machine Learning is a class I've been wanting to take ever since I was a freshman. My favorite aspect about the class is developing statistical models and algorithms to predict trends using data from previous years. Mr. Dagler is a really great mentor and teacher who guided me through the CS Pathway. Dagler has a huge emphasis on helping his students understand the difficult nature of computer science. Overall, I would definitely recommend taking this class!

Khloe
Class of 2025

I LIKED MR. DAGLER'S SUPER ENERGETIC AND MOTIVATED TEACHING

Owen
Class of 2022

i enjoyed the classification section, was fun to learn

Jeffrey
Class of 2022

I enjoyed going into the class in the early morning and doing the labs.

Kaylina
Class of 2022

This class intrigued me because we could code out programs that could make predictions as if the computer itself was learning and adapting from its mistakes. This class is offered at very little schools in California, so I would 100% take the opportunity to learn about Machine Learning with one of the nicest, and engaging teachers on campus.

Kyle Shun
Class of 2022

I liked learning about regression and dealing with multiple dimensions of data. I also liked finding trends in data only using input values. Each problem is a puzzle.

Jackson
Class of 2022

I enjoyed the project focus in the class, where I could spend time working independently with assistance where needed

Jaxon
Class of 2022

I enjoyed solving challenging problems and the collaborative environment of this class. Being able to work with my peers made the labs a lot more fun and engaging. This was an amazing class and I definitely would recommend it to others.

Matthew
Class of 2022

I really like doing the labs and seeing the results of models

Hannah
Class of 2022

I like the teamwork environment and the labs we do in class

Tyler
Class of 2022

I didn't know much about Machine Learning or about the coding language but after trying it out, I liked learning a new language and teaching with real life examples made coding easy to understand. It was amazing to create something of AI at my fingertips!

Jadyn
Class of 2022

What I like about Machine Learning is the experience that I had with this class. I wish for this class to continue improving and expanding throughout the years, hoping for more students to attend this class at some point.

Ethan
Class of 2022

I liked how easy it was. At first, this class seemed intimidating but after taking it for the 2 terms I had it, I learned to enjoy this class and not be feared by it. #TeamDagler

Kailyn
Class of 2022

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  • Gain an understanding of various ML models
  • Use regression to model continuous data
  • Predict discrete results using classification models
  • Discover unknown patters with clustering models
  • Additional topics include association rule learning, reinforcement learning, and natural language processing
Clay Dagler

Clay Dagler

CS & Robotics for Beginners | Exploring Computer Science | AP Computer Science A | Machine Learning Honors

As the head of the Computer Science pathway here at Franklin High, I hope to encourage my students to pursue a career in computer science. I started out teaching Math after graduating from the University of California, Davis, but slowly moved towards robotics and computer science, where I found engaged students learning more about mathematics. I've since worked as a CTE teacher with Franklin, finding any opportunities for my students to involve themselves with technology.