Explore the foundational building blocks of language problems
Learn to use Tensorflow to process languages
Learn to build Recurrent Neural Network models to predict sentiment
Learn and explore more advanced NLP topics such as LSTM
Requirements
No prior programming experience needed. You will learn directly in this class.
Description
This course is created to follow up with the AI4ALL initiatives. The course presents coding materials at a pre-college level and introduces a fundamental pipeline for a neural network model. The course is designed for the first-time learners and the audience who only want to get a taste of a machine learning project but still uncertain whether this is the career path. We will not bored you with the unnecessary component and we will directly take you through a list of topics that are fundamental for industry practitioners and researchers to design their customized neural network model. The course follows the previous sequence where we covered Artificial Neural Network models, Convolutional Neural Network models, and Image-to-Image models. This course focuses on some of the most basical tasks in language problems and develop the basic intuition of Recurrent Neural Networks.
This instructor team is lead by Ivy League graduate students and we have had 3+ years coaching high school students. We have seen all the ups and downs. Moreover, we want to share these roadblocks with you. This course is designed for beginner students at pre-college level who just want to have a quick taste of what AI is about and efficiently build a quick Github package to showcase some technical skills. We have other longer courses for more advanced students. However, we welcome anybody to take this course!
Who this course is for:
Pre-college level students interested in recurrent neural network models
Learn about the basics of Image-to-Image Network models without any prior knowledge
Learn to use python to design an Image-to-Image Network model without any prior knowledge
Learn from top tier Data Scientists to build Image-to-Image Network models for production
Learn to develop your own customized Image-to-Image Network models
Requirements
No prior programming experience needed. You will learn directly in this class.
Description
This course is created to follow up with the AI4ALL initiatives. The course presents coding materials at a pre-college level and introduces a fundamental pipeline for a neural network model. The course is designed for the first-time learners and the audience who only want to get a taste of a machine learning project but still uncertain whether this is the career path. We will not bored you with the unnecessary component and we will directly take you through a list of topics that are fundamental for industry practitioners and researchers to design their customized neural network model. The course focuses on the Image-to-Image Network models and introduce the important building block using Tensorflow. Important topics include Autoencoders, Variational Autoencoders, and U-net models.
This instructor team is lead by Ivy League graduate students and we have had 3+ years coaching high school students. We have seen all the ups and downs. Moreover, we want to share these roadblocks with you. This course is designed for beginner students at pre-college level who just want to have a quick taste of what AI is about and efficiently build a quick Github package to showcase some technical skills. We have other longer courses for more advanced students. However, we welcome anybody to take this course!
Who this course is for:
Pre-college level students interested in neural network models
Learn about the basics of Convolutional Neural Network models without any prior knowledge
Learn to use python to design a Convolutional Neural Network model without any prior knowledge
Learn from top tier Data Scientists to build Convolutional Neural Network models for production
Learn to develop your own customized Convolutional Neural Network models
Requirements
No prior programming experience needed. You will learn directly in this class.
Description
This course is created to follow up with the AI4ALL initiatives. The course presents coding materials at a pre-college level and introduces a fundamental pipeline for a neural network model. The course is designed for the first-time learners and the audience who only want to get a taste of a machine learning project but still uncertain whether this is the career path. We will not bored you with the unnecessary component and we will directly take you through a list of topics that are fundamental for industry practitioners and researchers to design their customized neural network model. The course focuses on Convolutional Neural Network models and introduce the important building block using Tensorflow.
This instructor team is lead by Ivy League graduate students and we have had 3+ years coaching high school students. We have seen all the ups and downs. Moreover, we want to share these roadblocks with you. This course is designed for beginner students at pre-college level who just want to have a quick taste of what AI is about and efficiently build a quick Github package to showcase some technical skills. We have other longer courses for more advanced students. However, we welcome anybody to take this course!
Who this course is for:
Pre-college level students interested in neural network models
