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Podcast: Machine Learning Guide
Episode:

001 Introduction
Category: Technology
Duration: 00:20:12
Publish Date: 2017-02-01 05:00:00
Description:

Links:

What is this podcast?

  • "Middle" level overview (deeper than a bird's eye view of machine learning; higher than math equations)
  • No math/programming experience required

Who is it for

  • Anyone curious about machine learning fundamentals
  • Aspiring machine learning developers

Why audio?

  • Supplementary content for commute/exercise/chores will help solidify your book/course-work

What it's not

Planned episodes

  • What is AI/ML: definition, comparison, history
  • Inspiration: automation, singularity, consciousness
  • ML Intuition: learning basics (infer/error/train); supervised/unsupervised/reinforcement; applications
  • Math overview: linear algebra, statistics, calculus
  • Linear models: supervised (regression, classification); unsupervised
  • Parts: regularization, performance evaluation, dimensionality reduction, etc
  • Deep models: neural networks, recurrent neural networks (RNNs), convolutional neural networks (convnets/CNNs)
  • Languages and Frameworks: Python vs R vs Java vs C/C++ vs MATLAB, etc; TensorFlow vs Torch vs Theano vs Spark, etc
Total Play: 0

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