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Study Group for Machine Learning / AI / Data Science
12th November, 2020
Last date to join: 30th November, 2020
Hi everyone, I've started a study/accountability group for people interested in learning more about machine learning, deep learning, artificial intelligence and data science in general. We've started an accountability program where we post our goals for the week/month. We have reading and study groups for specific topics and online courses (e.g. Coursera*). And we organize little coding challenges and virtual coding sessions to keep us motivated. We are still growing and happy about every new motivated member. Become part of our group, learn together with us, and make 2021 the year you finally become an AI expert.
Advanced-beginner
English
Description
The Deep Learning Specialization is a 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. In this Specialization, you will build and train neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more. Get ready to master theoretical concepts and their industry applications using Python and TensorFlow and tackle real-world cases such as speech recognition, music synthesis, chatbots, machine translation, natural language processing, and more. AI is transforming many industries. The Deep Learning Specialization provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career. Along the way, you will also get career advice from deep learning experts from industry and academia. Applied Learning Project By the end you’ll be able to: • Build and train deep neural networks, implement vectorized neural networks, identify architecture parameters, and apply DL to your applications • Use best practices to train and develop test sets and analyze bias/variance for building DL applications, use standard NN techniques, apply optimization algorithms, and implement a neural network in TensorFlow • Use strategies for reducing errors in ML systems, understand complex ML settings, and apply end-to-end, transfer, and multi-task learning • Build a Convolutional Neural Network, apply it to visual detection and recognition tasks, use neural style transfer to generate art, and apply these algorithms to image, video, and other 2D/3D data • Build and train Recurrent Neural Networks and its variants (GRUs, LSTMs), apply RNNs to character-level language modeling, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformers to perform Named Entity Recognition and Question Answering Read more
Deep Learning Specialization
Microcredentials 
Coursera
Free to Audit 
3 months at 10 hours a week 
Intermediate 
Paid Certificate Get notified about new study groups every week!
Study Group for Machine Learning / AI / Data Science
12th November, 2020
Last date to join: 30th November, 2020
Affiliate notice
Hi everyone, I've started a study/accountability group for people interested in learning more about machine learning, deep learning, artificial intelligence and data science in general. We've started an accountability program where we post our goals for the week/month. We have reading and study groups for specific topics and online courses (e.g. Coursera*). And we organize little coding challenges and virtual coding sessions to keep us motivated. We are still growing and happy about every new motivated member. Become part of our group, learn together with us, and make 2021 the year you finally become an AI expert.
Advanced-beginner
English
-
TypeMicrocredentials
-
ProviderCoursera
-
PricingFree to Audit
-
Duration3 months at 10 hours a week
-
DifficultyIntermediate
-
CertificatePaid Certificate
The Deep Learning Specialization is a 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.
In this Specialization, you will build and train neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more. Get ready to master theoretical concepts and their industry applications using Python and TensorFlow and tackle real-world cases such as speech recognition, music synthesis, chatbots, machine translation, natural language processing, and more.
AI is transforming many industries. The Deep Learning Specialization provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career. Along the way, you will also get career advice from deep learning experts from industry and academia.
Applied Learning Project
By the end you’ll be able to:
• Build and train deep neural networks, implement vectorized neural networks, identify architecture parameters, and apply DL to your applications
• Use best practices to train and develop test sets and analyze bias/variance for building DL applications, use standard NN techniques, apply optimization algorithms, and implement a neural network in TensorFlow
• Use strategies for reducing errors in ML systems, understand complex ML settings, and apply end-to-end, transfer, and multi-task learning
• Build a Convolutional Neural Network, apply it to visual detection and recognition tasks, use neural style transfer to generate art, and apply these algorithms to image, video, and other 2D/3D data
• Build and train Recurrent Neural Networks and its variants (GRUs, LSTMs), apply RNNs to character-level language modeling, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformers to perform Named Entity Recognition and Question Answering
Read more
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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
30th November, 2020
Get notified about new study groups every week!
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