Posts

Miniforge Cheat Sheet

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The core takeaway when using Miniforge is that mamba serves as a fast, drop-in replacement for conda, meaning you can swap the word conda for mamba in almost every environment and package management command. For optimal performance, use mamba to handle heavy lifting tasks like downloading, searching, and installing packages, and use conda for basic environment activation or shell initialization.  Here's a Miniforge Cheat Sheet created with AI's help.  It will cover the essential categories of your daily workflow. 1. Initialization Commands Before running operations, ensure Miniforge is properly integrated into your command line interface.  - conda init: Registers the package manager configuration to your specific shell or terminal program. - mamba init: Adds performance-optimized shell configurations tailored directly for Mamba-specific executions.  2. Environment Management Isolate distinct projects by organizing their dependencies inside standalone virtual runtime ...
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Miniforge Windows Update and Issue Fixed

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  I have not used Miniforge for some time. So I decided to update my last installation before using it. But when updating, I encountered a secure-connection issue on Windows. AI said, "The error schannel: the revocation status is unknown means my computer's built-in Windows security system (Schannel) cannot verify whether the SSL security certificates for the download servers have been revoked. This often happens after a long period of inactivity or due to strict corporate network rules." AI also gave me a list of fixes to try. I finally fixed the error using a temporary workaround - by turning off SSL verification entirely. I temporarily disabled SSL verification altogether just to get the system updated. Note: Turn this back on later for security. 1. Disable SSL check:     conda config --set ssl_verify false 2. Run updates:    conda update -n base -c conda-forge conda    mamba update mamba    mamba update --all 3. Important: Onc...
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Miniforge Windows 11 Setup and Time Bug Fix

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  (A) Here are the essentials of my Windows 11 Miniforge setup and fixation of an installation bug, together with useful links and command cheat sheet. 1. Windows 11 Miniforge Installation - Download the Windows installer (.exe) directly from the Conda-Forge GitHub.  - The Golden Rule: Always select "Just Me" (not "All Users") when prompted about who to install for. - Security Prompt: If Windows Defender SmartScreen blocks the app, just click "More Info" and then "Run Anyway". 2. Open Miniforge Prompt from the Windows Start Menu. Press Windows key, search for Miniforge Prompt, and click it. This is the only place where Python commands will work natively.   3. Follow basic rules and commands to keep computer safe and organized. - Protect the "Base" Environment: Always leave the base environment as it is. If it breaks, you will have to reinstall the app. - Create a sandbox (Environment): Create a separate environment named my_ai with Pyth...
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Minimalist AI Stack: Learning Python and AI with Vim and Miniforge

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  I have asked AI Collaborator to guess why I choose “Miniforge and VIM” for learning Python and AI by projects. This is its reply: It is because you want to build a rock-solid foundation by forcing yourself to understand how your code works under the hood, rather than relying on ‘magic’. Here is a guess at the psychology and strategy behind your setup: 1. You want to understand dependencies, not just hide them. Python environments, especially for AI (which relies on heavy libraries like PyTorch or TensorFlow), are notorious for dependency hell. The easy path: Anaconda or pipenv. Your path: Miniforge. You have chosen this because it gives you raw control. It forces you to learn how conda-forge packages things, how to isolate your AI projects using conda activate, and how to resolve version conflicts manually so you actually understand what your system is running. 2. You are prioritizing absolute focus and speed. AI development involves looking at a lot of text, code, and document...
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Introduction to Deep Learning. (Source: MIT.edu)

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MIT 6.S191 - Introduction to Deep Learning : Lecture 1, New 2025 Edition, Foundations of Deep Learning. Lecturer: Alexander Amini. Lectures, slides, and lab materials . I sat in for the interesting introduction of first lecture (and would continue this lecture later). Within the first few minutes, the lecturer demonstrated the power of deep learning and he motivated me to continue with this course ( I really hope I have the world of time.)
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What is deep learning? (Source: Mckinsey.com)

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Visit: What is Deep Learning? (Source: Mckinsey.com) An interesting write-out as it shares the relationship between deep learning and generative AI. It also introduces the kinds of neural networks are used in deep learning.
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Deep Learning

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Deep learning is a type of machine learning that uses multi-layered artificial neural networks to automatically learn patterns and features from vast amounts of data for complex tasks like image recognition, speech processing, and language translation It offers high accuracy by processing information in stages. Unlike traditional machine learning, it learns features directly from data without needing human-engineered feature extraction, making it powerful for unstructured data and complex problems. More on Deep Learning and Study Deep Learning  
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