Learning plan cover

Ai architecture modification

LEARNING PLAN

Ai architecture modification

This learning plan is essential for developers and data scientists looking to move beyond pre-built models into custom AI engineering. It provides a comprehensive roadmap from neural network basics to the sophisticated transformer designs and autonomous agent architectures that drive today's innovation.

ByCommunity User
2 h 54 m
12 coursesUpdated 6 days ago
Make your own neural networkHands-on Machine Learning With Scikit-learn And TensorflowFind Your Perfect AI Pathway12 sources

How This Learning Plan Was Made

This plan was crafted by BeFreed's proprietary AI to help you learn Ai architecture modification with ease. It is curated from in-depth research on the topic and structured around the most effective learning journeys proven by BeFreed users.

Each episode delivers bite-sized, high-impact lessons distilled from world-class sources — bestselling books, research papers, and expert insights. Together, they form a sophisticated yet accessible path to mastering Ai architecture modification.

What You'll Learn

  • Master the foundational building blocks of neural networks to create custom AI models.
  • Implement Transformer architectures and attention mechanisms used in modern LLMs.
  • Apply advanced optimization techniques to enhance model performance and efficiency.
  • Modify existing architectures to suit specialized industry applications and needs.
  • Design autonomous agents capable of complex reasoning and real-world problem solving.

Master the building blocks of AI systems by understanding how neural networks work from the ground up and learn to create your first working models.

Make your own neural network cover
Make your own neural network

Step-by-step guide to building neural networks for beginners.

8 m
Hands-on Machine Learning With Scikit-learn And Tensorflow cover
Hands-on Machine Learning With Scikit-learn And Tensorflow

Step-by-step guide to machine learning with Python

8 m
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Hands-On Machine Learning with Scikit-Learn and TensorFlowAI 2041How to Speak MachineLife 3.0
24 sources
Find Your Perfect AI Pathway

Explore the major AI subfields—from machine learning and data science to NLP and computer vision—and discover which specialization aligns with your unique skills and interests.

37 m

Dive deep into the revolutionary Transformer architecture and attention mechanisms that power today's most advanced AI systems like ChatGPT and GPT-4.

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LLM Interviews | EngineersOfAI — Technical Education for AI EngineersLLM Interview Questions | EngineersOfAI — The Engineering Curriculum for the AI EraTransformer Internals for LLMs | EngineersOfAI — The Engineering Curriculum for the AI EraThe LLM Engineering Field Guide: 45 Concepts Every Practitioner Needs - Edge of Context: Practical AI Engineering
7 sources
The AI Architect’s Playbook

Generic AI experience is no longer enough to stand out. Go inside the Transformer architecture to master the technical logic of the modern LLM.

18 m
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Attention Is All You Need - A Deep Dive into the Revolutionary ...Attention Is All You Need: Complete Guide to the Transformer Paper ...Attention Is All You Need: The Original Transformer ArchitectureHow RNNs Were Replaced by Transformers - And Why
6 sources
Attention Is All You Need: The AI Revolution

Discover how a 2017 paper with 8 authors and 173K citations transformed AI forever. From Google Translate to ChatGPT, explore the Transformer architecture that powers every modern AI system you use daily.

10 m
What Is ChatGPT Doing ... and Why Does It Work? cover
What Is ChatGPT Doing ... and Why Does It Work?

In-depth analysis of ChatGPT's AI mechanisms and effectiveness

9 m

Learn cutting-edge techniques for optimizing model performance, implementing architectural innovations, and fine-tuning systems for specific applications.

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Kimi-Linear : An Expressive, Efficient Attention ArchitectureAI Just Broke the Million-Token Barrier: How Kimi Linear's 6.3Kimi Linear: An Expressive, Efficient Attention Architecture | alphaXivKimi-Linear : Bye Bye Transformers | by Mehul Gupta - Medium
6 sources
Kimi Linear: The AI Architecture Revolution

Discover how Kimi Linear's breakthrough architecture processes million-token contexts 6.3x faster while using 75% less memory, potentially ending the era of traditional Transformers through intelligent forgetting and hybrid attention mechanisms.

7 m
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A Survey on Post-training of Large Language ModelsFine-tuning large language models for domain adaptation - NatureFine-tuning and Utilization Methods of Domain-specific LLMsPEFT, LoRA & QLoRA: Smarter, Faster Fine-Tuning for Domain LLMs
6 sources
AI Post-Training for Real-World Applications

Discover how businesses are transforming AI models for specific needs through parameter-efficient fine-tuning, domain adaptation, and practical implementation strategies that deliver measurable results.

10 m
Keras Reinforcement Learning Projects cover
Keras Reinforcement Learning Projects

Build self-learning AI agents with 9 reinforcement learning projects using Keras.

9 m

Build sophisticated AI architectures that go beyond simple models to create autonomous agents capable of complex reasoning and real-world problem solving.

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Notion Rebuilt Its AI Agent System 5 Times Before Launch — BigGo FinanceNotion’s Token Town: 5 Rebuilds, 100+ Tools, MCP vs CLIs and the Software Factory Future — Simon Last & Sarah Sachs of NotionNotion AI Agent Architecture: 5 Rebuilds, 100+ Tools, and What Finally Worked | OpenNash BlogHow we built security into Custom Agents
7 sources
Notion’s Autonomous Agent Refactor

Traditional software design fails autonomous agents. Learn how Notion rebuilt its architecture five times to create reliable, high-scale AI workflows.

20 m
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Keras Reinforcement Learning ProjectsAutomating Salesforce Marketing CloudChatGPT for DummiesArtificial Intelligence and Generative AI for Beginners
19 sources
Building AI agents that actually do the work

Stop using LLMs as simple chatbots. Learn how to build autonomous agents that use tools and APIs to handle complex workflows and solve real problems.

29 m
Superintelligence cover
Superintelligence

The potential risks and benefits of advanced AI

9 m

Discover more

Ai learning

Ai learning

LEARNING PLAN

Ai learning

As AI reshapes every industry, understanding its technical core and ethical boundaries is no longer optional. This plan is ideal for professionals and tech enthusiasts who want to transition from passive users to active creators of intelligent systems.

2 h 8 m4 Sections
Learning about Ai

Learning about Ai

LEARNING PLAN

Learning about Ai

As artificial intelligence becomes a cornerstone of modern industry, understanding its technical and ethical foundations is essential for staying competitive. This plan is ideal for professionals and enthusiasts looking to transition from basic awareness to building and managing intelligent systems.

2 h 40 m4 Sections
Transformers

Transformers

LEARNING PLAN

Transformers

This learning plan is essential for developers and tech enthusiasts looking to master the technology driving the current AI boom. It bridges the gap between theoretical neural networks and practical implementation of state-of-the-art Large Language Models.

4 h 17 m5 Sections
我想学习ai

我想学习ai

LEARNING PLAN

我想学习ai

This comprehensive roadmap bridges the gap between theoretical AI concepts and hands-on technical implementation. It is ideal for aspiring developers and tech enthusiasts looking to transition from basic understanding to building advanced neural networks.

3 h 47 m4 Sections
Master AI Efficiency and Effectiveness

Master AI Efficiency and Effectiveness

LEARNING PLAN

Master AI Efficiency and Effectiveness

This learning plan is essential for professionals and leaders aiming to stay competitive in an increasingly automated economy. It provides a comprehensive roadmap from foundational theory to building advanced autonomous systems, making it ideal for anyone looking to lead digital transformation.

4 h 9 m4 Sections
Explore Local AI Models and Infrastructure

Explore Local AI Models and Infrastructure

LEARNING PLAN

Explore Local AI Models and Infrastructure

This plan is essential for developers and IT architects who need to maintain data sovereignty while leveraging powerful AI capabilities. It bridges the gap between theoretical model building and the practical infrastructure required to run private, secure, and automated AI systems.

3 h 20 m4 Sections
To build a new ai acitecture

To build a new ai acitecture

LEARNING PLAN

To build a new ai acitecture

This curriculum is essential for engineers and researchers aiming to move beyond pre-built models to architecting original AI systems. It provides the technical depth required to design scalable, agentic, and transformer-based solutions for the next generation of intelligent software.

3 h 19 m4 Sections
Ai tech and how to use it

Ai tech and how to use it

LEARNING PLAN

Ai tech and how to use it

This learning plan is essential for professionals and creators looking to bridge the gap between AI curiosity and technical mastery. It benefits anyone from beginners wanting to use practical tools to aspiring developers ready to build complex neural networks.

3 h 25 m4 Sections

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