Machine Learning Guide1 Feb 2017

MLG 001 Introduction

Show notes: ocdevel.com/mlg/1. MLG teaches the fundamentals of machine learning and artificial intelligence. It covers intuition, models, math, languages, frameworks, etc. Where your other ML resources provide the trees, I provide the forest. Consider MLG your syllabus, with highly-curated resources for each episode's details at ocdevel.com. Audio is a great supplement during exercise, commute, chores, etc.

MLG, Resources Guide
Gnothi (podcast project): website, Github

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

News and Interviews: TWiML and AI, O'Reilly Data Show, Talking machines
Misc Topics: Linear Digressions, Data Skeptic, Learning machines 101
iTunesU issues

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

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Avsnitt(60)

MLA 030 AI Job Displacement & ML Careers

ML engineering demand remains high with a 3.2 to 1 job-to-candidate ratio, but entry-level hiring is collapsing as AI automates routine programming and data tasks. Career longevity requires shifting f...

26 Feb 42min

MLA 029 OpenClaw

OpenClaw is a self-hosted AI agent daemon that executes autonomous tasks through messaging apps like WhatsApp and Telegram using persistent memory. It integrates with Claude Code to enable software de...

22 Feb 51min

MLA 028 AI Agents

AI agents differ from chatbots by pursuing autonomous goals through the ReACT loop rather than responding to turn-based prompts. While coding agents are currently the most reliable due to verifiable f...

22 Feb 37min

MLA 027 AI Video End-to-End Workflow

How to maintain character consistency, style consistency, etc in an AI video. Prosumers can use Google Veo 3's "High-Quality Chaining" for fast social media content. Indie filmmakers can achieve narra...

14 Juli 20251h 11min

MLA 026 AI Video Generation: Veo 3 vs Sora, Kling, Runway, Stable Video Diffusion

Google Veo leads the generative video market with superior 4K photorealism and integrated audio, an advantage derived from its YouTube training data. OpenAI Sora is the top tool for narrative storytel...

12 Juli 202540min

MLA 025 AI Image Generation: Midjourney vs Stable Diffusion, GPT-4o, Imagen & Firefly

The AI image market has split: Midjourney creates the highest quality artistic images but fails at text and precision. For business use, OpenAI's GPT-4o offers the best conversational control, while A...

9 Juli 20251h 12min

MLG 036 Autoencoders

Auto encoders are neural networks that compress data into a smaller "code," enabling dimensionality reduction, data cleaning, and lossy compression by reconstructing original inputs from this code. Ad...

30 Maj 20251h 5min

MLG 035 Large Language Models 2

At inference, large language models use in-context learning with zero-, one-, or few-shot examples to perform new tasks without weight updates, and can be grounded with Retrieval Augmented Generation ...

8 Maj 202545min