Introduz backpropagation a partir do uso de Derivada Parciais em grafos.
Calculus on Computational Graphs: Backpropagation
(03.04.17)
http://cs231n.github.io/optimization-2
Yes you should understand backprop
Mais um [14.05.17]
http://daniel-at-world.blogspot.com.br/2017/02/ai-implement-your-own-automatic.html
Outro [06/12/2017]
https://medium.com/@karpathy/yes-you-should-understand-backprop-e2f06eab496b
quarta-feira, 25 de janeiro de 2017
Ótima introdução ao Backpropagation
Marcadores:
AM,
Derivadas Parciais,
Grafos,
Matemática,
Redes Neurais
terça-feira, 24 de janeiro de 2017
Plano de Estudo para se tornar um Cientista de Dados
Sugestão de um roteiro de estudo para se tornar um cientisa de dados, muito bom.
The most comprehensive Data Science learning plan for 2017
Beginner’s Path for 2017
Sugestão de Leituras
How to train your mind for analytical thinking?
Your Guide to Master Hypothesis Testing in Statistics
Useful tools to improve structured thinking
The 10 Statistical Techniques Data Scientists Need to Master
The most comprehensive Data Science learning plan for 2017
Beginner’s Path for 2017
- Step 1: Getting started and testing the waters
- Step 2: Mathematics & Statistics
- Introdução à Estatística Descritiva - Step 3: Introducing the tool – R / Python
- Step 4: Basic & Advanced machine learning tools
- Step 5: Building your profile
- Step 6: Applying for Jobs / Internships
- Step 1: Assessing your technical & Structured thinking skills
- Step 2: A few more ML algorithms
- Step 3: Pick up a data visualization tool
- Step 4: Big Data tools and techniques
- Step 5: Deep Learning Basic and Advanced
- Step 6: Reinforcement Learning
- Step 7: Web frameworks & Cloud Computing
Sugestão de Leituras
How to train your mind for analytical thinking?
Your Guide to Master Hypothesis Testing in Statistics
Useful tools to improve structured thinking
The 10 Statistical Techniques Data Scientists Need to Master
Marcadores:
AM,
DataMining,
Machine Learning,
ML,
Python
Assinar:
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