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Study Partner for Stanford, MIT and Coursera Deep Learning Courses
10th April, 2023
Last date to join: 20th July, 2024
Hello everyone. I am looking for a study partner to watch lectures and attempt assignments for CS230, CS231n (Stanford courses on deep learning and computer vision) and Coursera deep learning specialization. In the longer run, I want to nail down machine learning Stanford course, machine learning Coursera specialization and multimodal machine learning course from MIT. Anyone up to become a study partner? I have over 2 years of work experience in CV but never got the chance to attempt these courses end to end.
Advanced-beginner
English
Description
In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI.
Syllabus
- Introduction to Deep Learning
- Analyze the major trends driving the rise of deep learning, and give examples of where and how it is applied today.
- Neural Networks Basics
- Set up a machine learning problem with a neural network mindset and use vectorization to speed up your models.
- Shallow Neural Networks
- Build a neural network with one hidden layer, using forward propagation and backpropagation.
- Deep Neural Networks
- Analyze the key computations underlying deep learning, then use them to build and train deep neural networks for computer vision tasks.
Neural Networks and Deep Learning
Online Courses 
Coursera
Free to Audit 
1 day 35 minutes 
Intermediate 
Paid Certificate Get notified about new study groups every week!
Study Partner for Stanford, MIT and Coursera Deep Learning Courses
10th April, 2023
Last date to join: 20th July, 2024
Affiliate notice
Hello everyone. I am looking for a study partner to watch lectures and attempt assignments for CS230, CS231n (Stanford courses on deep learning and computer vision) and Coursera deep learning specialization. In the longer run, I want to nail down machine learning Stanford course, machine learning Coursera specialization and multimodal machine learning course from MIT. Anyone up to become a study partner? I have over 2 years of work experience in CV but never got the chance to attempt these courses end to end.
Advanced-beginner
English
-
TypeOnline Courses
-
ProviderCoursera
-
PricingFree to Audit
-
Duration1 day 35 minutes
-
DifficultyIntermediate
-
CertificatePaid Certificate
In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI.
- Introduction to Deep Learning
- Analyze the major trends driving the rise of deep learning, and give examples of where and how it is applied today.
- Neural Networks Basics
- Set up a machine learning problem with a neural network mindset and use vectorization to speed up your models.
- Shallow Neural Networks
- Build a neural network with one hidden layer, using forward propagation and backpropagation.
- Deep Neural Networks
- Analyze the key computations underlying deep learning, then use them to build and train deep neural networks for computer vision tasks.
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Frequently asked questions
Yes. Our study groups (all of them) are free to join
You join the group and study the MOOC together on a schedule. The exact dates, deadlines, are created by the host
This depends on the host of your group. Some groups have weekly video calls for accountability + doubt solving.
Moocable is a community where you can find study partners, mentors, or people to collaborate on projects. It's designed for people who want to upskill, but struggle with self-learning. Users often post about their skills, goals, and what they're looking to learn or work on, and others can respond to form partnerships or groups. You can join our community
20th July, 2024
Get notified about new study groups every week!
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