scrapbook
  • "Unorganized" Notes
  • The Best Public Datasets for Machine Learning and Data Science
  • Practice Coding
  • plaid-API project
  • Biotech
    • Machine Learning vs. Deep Learning
  • Machine Learning for Computer Graphics
  • Books (on GitHub)
  • Ideas/Thoughts
  • Ziva for feature animation: Stylized simulation and machine learning-ready workflows
  • Tools
  • 🪶math
    • Papers
    • Math for ML (coursera)
      • Linear Algebra
        • Wk1
        • Wk2
        • Wk3
        • Wk4
        • Wk5
      • Multivariate Calculus
    • Improving your Algorithms & Data Structure Skills
    • Algorithms
    • Algorithms (MIT)
      • Lecture 1: Algorithmic Thinking, Peak Finding
    • Algorithms (khan academy)
      • Binary Search
      • Asymptotic notation
      • Sorting
      • Insertion sort
      • Recursion
      • Solve Hanoi recursively
      • Merge Sort
      • Representing graphs
      • The breadth-first search algorithm
      • Breadth First Search in JavaScript
      • Breadth-first vs Depth-first Tree Traversal in Javascript
    • Algorithms (udacity)
      • Social Network
    • Udacity
      • Linear Algebra Refresher /w Python
    • math-notes
      • functions
      • differential calculus
      • derivative
      • extras
      • Exponentials & logarithms
      • Trigonometry
    • Probability (MIT)
      • Unit 1
        • Probability Models and Axioms
        • Mathematical background: Sets; sequences, limits, and series; (un)countable sets.
    • Statistics and probability (khan academy)
      • Analyzing categorical data
      • Describing and comparing distributions
      • Outliers Definition
      • Mean Absolute Deviation (MAD)
      • Modeling data distribution
      • Exploring bivariate numerical data
      • Study Design
      • Probability
      • Counting, permutations, and combinations
      • Binomial variables
        • Binomial Distribution
        • Binomial mean and standard deviation formulas
        • Geometric random variable
      • Central Limit Theorem
      • Significance Tests (hypothesis testing)
    • Statistics (hackerrank)
      • Mean, Medium, Mode
      • Weighted Mean
      • Quartiles
      • Standard Deviation
      • Basic Probability
      • Conditional Probability
      • Permutations & Combinations
      • Binomial Distribution
      • Negative Binomial
      • Poisson Distribution
      • Normal Distribution
      • Central Limit Theorem
      • Important Concepts in Bayesian Statistics
  • 📽️PRODUCT
    • Product Strategy
    • Product Design
    • Product Development
    • Product Launch
  • 👨‍💻coding
    • of any interest
    • Maya API
      • Python API
    • Python
      • Understanding Class Inheritance in Python 3
      • 100+ Python challenging programming exercises
      • coding
      • Iterables vs. Iterators vs. Generators
      • Generator Expression
      • Stacks (LIFO) / Queues (FIFO)
      • What does -1 mean in numpy reshape?
      • Fold Left and Right in Python
      • Flatten a nested list of lists
      • Flatten a nested dictionary
      • Traverse A Tree
      • How to Implement Breadth-First Search
      • Breadth First Search
        • Level Order Tree Traversal
        • Breadth First Search or BFS for a Graph
        • BFS for Disconnected Graph
      • Trees and Tree Algorithms
      • Graph and its representations
      • Graph Data Structure Interview Questions
      • Graphs in Python
      • GitHub Repo's
    • Python in CG Production
    • GLSL/HLSL Shading programming
    • Deep Learning Specialization
      • Neural Networks and Deep Learning
      • Untitled
      • Untitled
      • Untitled
    • TensorFlow for AI, ML, and DL
      • Google ML Crash Course
      • TensorFlow C++ API
      • TensorFlow - coursera
      • Notes
      • An Introduction to different Types of Convolutions in Deep Learning
      • One by One [ 1 x 1 ] Convolution - counter-intuitively useful
      • SqueezeNet
      • Deep Compression
      • An Overview of ResNet and its Variants
      • Introducing capsule networks
      • What is a CapsNet or Capsule Network?
      • Xception
      • TensorFlow Eager
    • GitHub
      • Project README
    • Agile - User Stories
    • The Open-Source Data Science Masters
    • Coding Challenge Websites
    • Coding Interview
      • leetcode python
      • Data Structures
        • Arrays
        • Linked List
        • Hash Tables
        • Trees: Basic
        • Heaps, Stacks, Queues
        • Graphs
          • Shortest Path
      • Sorting & Searching
        • Depth-First Search & Breadth-First Search
        • Backtracking
        • Sorting
      • Dynamic Programming
        • Dynamic Programming: Basic
        • Dynamic Programming: Advanced
    • spaCy
    • Pandas
    • Python Packages
    • Julia
      • jupyter
    • macos
    • CPP
      • Debugging
      • Overview of memory management problems
      • What are lvalues and rvalues?
      • The Rule of Five
      • Concurrency
      • Avoiding Data Races
      • Mutex
      • The Monitor Object Pattern
      • Lambdas
      • Maya C++ API Programming Tips
      • How can I read and parse CSV files in C++?
      • Cpp NumPy
    • Advanced Machine Learning
      • Wk 1
      • Untitled
      • Untitled
      • Untitled
      • Untitled
  • data science
    • Resources
    • Tensorflow C++
    • Computerphile
      • Big Data
    • Google ML Crash Course
    • Kaggle
      • Data Versioning
      • The Basics of Rest APIs
      • How to Make an API
      • How to deploying your API
    • Jupiter Notebook Tips & Tricks
      • Jupyter
    • Image Datasets Notes
    • DS Cheatsheets
      • Websites & Blogs
      • Q&A
      • Strata
      • Data Visualisation
      • Matplotlib etc
      • Keras
      • Spark
      • Probability
      • Machine Learning
        • Fast Computation of AUC-ROC score
    • Data Visualisation
    • fast.ai
      • deep learning
      • How to work with Jupyter Notebook on a remote machine (Linux)
      • Up and Running With Fast.ai and Docker
      • AWS
    • Data Scientist
    • ML for Beginners (Video)
    • ML Mastery
      • Machine Learning Algorithms
      • Deep Learning With Python
    • Linear algebra cheat sheet for deep learning
    • DL_ML_Resources
    • Awesome Machine Learning
    • web scraping
    • SQL Style Guide
    • SQL - Tips & Tricks
  • 💡Ideas & Thoughts
    • Outdoors
    • Blog
      • markdown
      • How to survive your first day as an On-set VFX Supervisor
    • Book Recommendations by Demi Lee
  • career
    • Skills
    • learn.co
      • SQL
      • Distribution
      • Hypothesis Testing Glossary
      • Hypothesis Tests
      • Hypothesis & AB Testing
      • Combinatorics Continued and Maximum Likelihood Estimation
      • Bayesian Classification
      • Resampling and Monte Carlo Simulation
      • Extensions To Linear Models
      • Time Series
      • Distance Metrics
      • Graph Theory
      • Logistic Regression
      • MLE (Maximum Likelihood Estimation)
      • Gradient Descent
      • Decision Trees
      • Ensemble Methods
      • Spark
      • Machine Learning
      • Deep Learning
        • Backpropagation - math notation
        • PRACTICE DATASETS
        • Big Data
      • Deep Learning Resources
      • DL Datasets
      • DL Tutorials
      • Keras
      • Word2Vec
        • Word2Vec Tutorial Part 1 - The Skip-Gram Model
        • Word2Vec Tutorial Part 2 - Negative Sampling
        • An Intuitive Explanation of Convolutional Neural Networks
      • Mod 4 Project
        • Presentation
      • Mod 5 Project
      • Capstone Project Notes
        • Streaming large training and test files into Tensorflow's DNNClassifier
    • Carrier Prep
      • The Job Search
        • Building a Strong Job Search Foundation
        • Key Traits of Successful Job Seekers
        • Your Job Search Mindset
        • Confidence
        • Job Search Action Plan
        • CSC Weekly Activity
        • Managing Your Job Search
      • Your Online Presence
        • GitHub
      • Building Your Resume
        • Writing Your Resume Summary
        • Technical Experience
      • Effective Networking
        • 30 Second Elevator Pitch
        • Leveraging Your Network
        • Building an Online Network
        • Linkedin For Research And Networking
        • Building An In-Person Network
        • Opening The Line Of Communication
      • Applying to Jobs
        • Applying To Jobs Online
        • Cover Letters
      • Interviewing
        • Networking Coffees vs Formal Interviews
        • The Coffee Meeting/ Informational Interview
        • Communicating With Recruiters And HR Professional
        • Research Before an Interview
        • Preparing Questions for Interviews
        • Phone And Video/Virtual Interviews
        • Cultural/HR Interview Questions
        • The Salary Question
        • Talking About Apps/Projects You Built
        • Sending Thank You's After an Interview
      • Technical Interviewing
        • Technical Interviewing Formats
        • Code Challenge Best Practices
        • Technical Interviewing Resources
      • Communication
        • Following Up
        • When You Haven't Heard From an Employer
      • Job Offers
        • Approaching Salary Negotiations
      • Staying Current in the Tech Industry
      • Module 6 Post Work
      • Interview Prep
  • projects
    • Text Classification
    • TERRA-REF
    • saildrone
  • Computer Graphics
  • AI/ML
  • 3deeplearning
    • Fast and Deep Deformation Approximations
    • Compress and Denoise MoCap with Autoencoders
    • ‘Fast and Deep Deformation Approximations’ Implementation
    • Running a NeuralNet live in Maya in a Python DG Node
    • Implement a Substance like Normal Map Generator with a Convolutional Network
    • Deploying Neural Nets to the Maya C++ API
  • Tools/Plugins
  • AR/VR
  • Game Engine
  • Rigging
    • Deformer Ideas
    • Research
    • brave rabbit
    • Useful Rigging Links
  • Maya
    • Optimizing Node Graph for Parallel Evaluation
  • Houdini
    • Stuff
    • Popular Built-in VEX Attributes (Global Variables)
Powered by GitBook
On this page
  1. career
  2. learn.co
  3. Deep Learning

Backpropagation - math notation

PreviousDeep LearningNextPRACTICE DATASETS

Last updated 6 years ago

Calculations