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Machine Learning Guide
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Machine Learning Guide

Author: OCDevel

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Description

Teaches the high level fundamentals of machine learning and artificial intelligence. I teach basic intuition, algorithms, and math. I discuss languages and frameworks, deep learning, and more. Audio may seem inferior, but it's a great supplement during exercise/commute/chores. Where your other resources provide the machine learning trees, I provide the forest. Consider me your syllabus. At the end of every episode I provide high-quality curated resources for learning each episode’s details.
30 Episodes
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MLG: I'm rebooting this series to fix mistakes & add more shallows (Bayesian methods, Tree methods, etc). I'm adding Patreon rewards, including access to a new podcast series: Machine Learning Applied, discussing applied/practical 10-20m frequent episodes. ocdevel.com/mlg/30 for notes and resources
Introduction to reinforcement learning concepts. ocdevel.com/mlg/29 for notes and resources.
028 Hyperparameters 2

028 Hyperparameters 2

2018-02-0400:50:101

Hyperparameters part 2: hyper-search, regularization, SGD optimizers, scaling. ocdevel.com/mlg/28 for notes and resources
027 Hyperparameters 1

027 Hyperparameters 1

2018-01-2800:46:093

Hyperparameters part 1: network architecture. ocdevel.com/mlg/27 for notes and resources
026 Project Bitcoin Trader

026 Project Bitcoin Trader

2018-01-2700:38:201

Community project & intro to Bitcoin/crypto + trading. ocdevel.com/mlg/26 for notes and resources
Convnets or CNNs. Filters, feature maps, window/stride/padding, max-pooling. ocdevel.com/mlg/25 for notes and resources
024 Tech Stack

024 Tech Stack

2017-10-0701:01:173

TensorFlow, Pandas, Numpy, Scikit-Learn, Keras, TensorForce. ocdevel.com/mlg/24 for notes and resources
023 Deep NLP 2

023 Deep NLP 2

2017-08-2000:42:454

RNN review, bi-directional RNNs, LSTM & GRU cells. ocdevel.com/mlg/23 for notes and resources
022 Deep NLP 1

022 Deep NLP 1

2017-07-2900:49:214

Recurrent Neural Networks (RNNs) and Word2Vec. ocdevel.com/mlg/22 for notes and resources
Introducing a new podcast series on Patreon: Machine Learning Applied. ocdevel.com/mlg/21 for notes and resources
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Comments (22)

Sam Osborne

good work mate this is fantastic.. very informative and has helped me get concepts that I couldn't otherwise through self study.. I what to give you 10$ in return

Jun 18th
Reply

Alexandre Shimono

Hey, I started listening to your podcast recently, and noticed you haven't published any new episode over the last year or so. Any chances you will come back some day? PS: high-quality material, really appreciated it!

May 25th
Reply

simon abdou

an awesome and clear summary of RL. Thank you

May 6th
Reply

Eduard Kumpan

I was sceptical if hearing how an algorithm works will make me understand it, but you did a great job explaining it!

Apr 3rd
Reply

Amir Shirazi

professional work and very good quality in all aspects. thanks!

Feb 28th
Reply

Khaing Win

can you make an episode on the latest Google self attention mechanism in neural machine translation?

Dec 31st
Reply

Mahamad El Tanahy

Definitely the best podcast on machine learning. great job!

Oct 29th
Reply

alireza bayat

simply amazing , appreciate for your brilliant podcasts

Oct 9th
Reply

112358 132134

Thank you, dude! Awesome. Your podcasts are really helpful :)

Aug 14th
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Edgar Scott

your descriptions are better than some of the moocs on udemy!!!

Aug 8th
Reply

Ivan Raszl

Well done!

Jun 29th
Reply

Martin Larsson

Super helpful and easy listening. You rock!

Jun 17th
Reply

Mari Subramanian

thanks for this. this is gold

May 3rd
Reply

Siva Sukumar Reddy

so far, the best source for machine learning

Apr 13th
Reply

Scott Parker

This has been a really helpful podcast, thank you for interesting your time!

Mar 22nd
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Sankarshan Sen

thanks for the podcast, brilliant work

Feb 6th
Reply

g3n c0d3r

Simply amazed at how well I was able to visualize the whole concept even though it's just audio. Keep up the good work!

Jan 29th
Reply

Tim O'Hagan

Really great explanations! Very well done!

Jan 23rd
Reply

Pete Clayton

Great quality. Very easy to follow and moves at a good pace. Great introduction.

Jan 7th
Reply

Gustavo Barros

Good job dude, amazing

Dec 29th
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