Machine Learning Guide
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Machine Learning Guide
Machine learning audio course, teaching the fundamentals of machine learning and artificial intelligence. It covers intuition, models (shallow and deep), math, languages, frameworks, etc. Where your other ML resources provide the trees, I provide the forest. Consider MLG your syllabus, with highly-c...
Episodi recenti
57 episodi
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...
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....
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-...
MLG 036 Autoencoders
Auto encoders are neural networks that compress data into a smaller "code," enabling dimensionality reduction, data cleaning, and lossy compression by...
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 ca...
MLG 034 Large Language Models 1
Explains language models (LLMs) advancements. Scaling laws - the relationships among model size, data size, and compute - and how emergent abilities s...
MLA 024 Code AI MCP Servers, ML Engineering
Tool use in code AI agents allows for both in-editor code completion and agent-driven file and command actions, while the Model Context Protocol (MCP)...
MLA 023 Code AI Models & Modes
Gemini 2.5 Pro currently leads in both accuracy and cost-effectiveness among code-focused large language models, with Claude 3.7 and a DeepSeek R1/Cla...
MLA 022 Code AI: Cursor, Cline, Roo, Aider, Copilot, Windsurf
Vibe coding is using large language models within IDEs or plugins to generate, edit, and review code, and has recently become a prominent and evolving...
MLA 021 Databricks: Cloud Analytics and MLOps
Databricks is a cloud-based platform for data analytics and machine learning operations, integrating features such as a hosted Spark cluster, Python n...
MLA 020 Kubeflow and ML Pipeline Orchestration on Kubernetes
Machine learning pipeline orchestration tools, such as SageMaker and Kubeflow, streamline the end-to-end process of data ingestion, model training, de...
MLA 019 Cloud, DevOps & Architecture
The deployment of machine learning models for real-world use involves a sequence of cloud services and architectural choices, where machine learning e...
MLA 017 AWS Local Development Environment
AWS development environments for local and cloud deployment can differ significantly, leading to extra complexity and setup during cloud migration. By...
MLA 016 AWS SageMaker MLOps 2
SageMaker streamlines machine learning workflows by enabling integrated model training, tuning, deployment, monitoring, and pipeline automation within...
MLA 015 AWS SageMaker MLOps 1
SageMaker is an end-to-end machine learning platform on AWS that covers every stage of the ML lifecycle, including data ingestion, preparation, traini...
MLA 014 Machine Learning Hosting and Serverless Deployment
Machine learning model deployment on the cloud is typically handled with solutions like AWS SageMaker for end-to-end training and inference as a REST...
MLA 013 Tech Stack for Customer-Facing Machine Learning Products
Primary technology recommendations for building a customer-facing machine learning product include React and React Native for the front end, serverles...
MLA 012 Docker for Machine Learning Workflows
Docker enables efficient, consistent machine learning environment setup across local development and cloud deployment, avoiding many pitfalls of virtu...
MLG 032 Cartesian Similarity Metrics
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Show notes at ocdevel.com/mlg/32.
L1/L2 norm, Manhattan, Euclidean, cosine dis...
MLA 011 Practical Clustering Tools
Primary clustering tools for practical applications include K-means using scikit-learn or Faiss, agglomerative clustering leveraging cosine similarity...
MLA 010 NLP packages: transformers, spaCy, Gensim, NLTK
The landscape of Python natural language processing tools has evolved from broad libraries like NLTK toward more specialized packages such as Gensim f...
MLA 009 Charting and Visualization Tools for Data Science
Python charting libraries - Matplotlib, Seaborn, and Bokeh - explaining, their strengths from quick EDA to interactive, HTML-exported visualizations,...
MLA 008 Exploratory Data Analysis (EDA)
Exploratory data analysis (EDA) sits at the critical pre-modeling stage of the data science pipeline, focusing on uncovering missing values, detecting...
MLA 007 Jupyter Notebooks
Jupyter Notebooks, originally conceived as IPython Notebooks, enable data scientists to combine code, documentation, and visual outputs in an interact...
MLA 006 Salaries for Data Science & Machine Learning
O'Reilly's 2017 Data Science Salary Survey finds that location is the most significant salary determinant for data professionals, with median salaries...
MLA 005 Shapes and Sizes: Tensors and NDArrays
Explains the fundamental differences between tensor dimensions, size, and shape, clarifying frequent misconceptions—such as the distinction between th...
MLA 001 Degrees, Certificates, and Machine Learning Careers
While industry-respected credentials like Udacity Nanodegrees help build a practical portfolio for machine learning job interviews, they remain insuff...
MLA 003 Storage: HDF, Pickle, Postgres
Practical workflow of loading, cleaning, and storing large datasets for machine learning, moving from ingesting raw CSVs or JSON files with pandas to...
MLA 002 Numpy & Pandas
NumPy enables efficient storage and vectorized computation on large numerical datasets in RAM by leveraging contiguous memory allocation and low-level...
MLG 029 Reinforcement Learning Intro
Notes and resources: ocdevel.com/mlg/29
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Reinforcement Learning (RL) is a fu...
MLG 028 Hyperparameters 2
Notes and resources: ocdevel.com/mlg/28
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More hyperparameters for optimizin...
MLG 027 Hyperparameters 1
Full notes and resources at ocdevel.com/mlg/27
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Hyperparameters are crucial...
MLG 026 Project Bitcoin Trader
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Ful notes and resources at ocdevel.com/mlg/26
NOTE. This episode is no long...
MLG 025 Convolutional Neural Networks
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Notes and resources at ocdevel.com/mlg/25
Filters and Feature Maps: Filters...
MLG 024 Tech Stack
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Notes and resources at ocdevel.com/mlg/24
Desktop if you're stationary, as...
MLG 023 Deep NLP 2
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Notes and resources at ocdevel.com/mlg/23
Vanilla Neural Networks (Feedforw...
MLG 022 Deep NLP 1
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Notes and resources at ocdevel.com/mlg/22
Deep NLP Fundamentals
Deep...
MLG 020 Natural Language Processing 3
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Notes and resources at ocdevel.com/mlg/20
NLP progresses through three main...
MLG 019 Natural Language Processing 2
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Notes and resources at ocdevel.com/mlg/19
Classical NLP Techniques:
O...