名古屋のFine-Tuningトレーニング

Online or onsite, instructor-led live Fine-Tuning training courses demonstrate through interactive hands-on practice how to use customized machine learning models to optimize performance for specific tasks, datasets, or applications.

Fine-Tuning training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Fine-Tuning training can be carried out locally on customer premises in 名古屋 or in NobleProg corporate training centers in 名古屋.

NobleProg -- Your Local Training Provider

Image of NobleProg Training Place, City Nagoya - Meieki Minami

〒450-0002愛知県名古屋市中村区名駅5-31-10リンクス名駅ビル 5階・6階, 名古屋, 日本, 450-0002

日本第三の都市、愛知県名古屋市。そのターミナル駅である名古屋駅の中心地、名駅エリアに「オープンオフィス名駅東」は位置します。名駅エリアは2015年から2017年にかけて、大型オフィスが続けて竣工し、多くの企業が、この名駅エリアに集まることが予想されています。さらには、2027年のリニア新幹線開通を控え、いま、最も注目を浴びている街の一つです。名古屋といえば、トヨタ自動車をはじめとした自動車製造業の本拠地として、世界的にも有名です。自動車だけでなく、名古屋には日本を代表する多くの製造業の本社があり、関連企業やパートナー企業も含め、製造業を中心としたビジネスタウンが形成されています。また近年では、IT関連業の名古屋進出も多くなっております。再開発の注目度だけでなく、東京・大阪・各都市へのアクセス、通勤・営業活動にも便利な名駅エリアは、人気の高いビジネスエリアになっています。利用可能なサービス

Explore Our Courses

Fine-Tuning Vision-Language Models (VLMs)

14 時間

Safety and Bias Mitigation in Fine-Tuned Models

14 時間

Fine-Tuning for Retrieval-Augmented Generation (RAG) Systems

14 時間

Fine-Tuning Open-Source LLMs (LLaMA, Mistral, Qwen, etc.)

14 時間

Parameter-Efficient Fine-Tuning (PEFT) Techniques for LLMs

14 時間

Fine-Tuning Large Language Models Using QLoRA

14 時間

Fine-Tuning with Reinforcement Learning from Human Feedback (RLHF)

14 時間

Domain-Specific Fine-Tuning for Finance

21 時間

Troubleshooting Fine-Tuning Challenges

14 時間

Optimizing Large Models for Cost-Effective Fine-Tuning

21 時間

Prompt Engineering and Few-Shot Fine-Tuning

14 時間

Fine-Tuning Multimodal Models

28 時間

Fine-Tuning DeepSeek LLM for Custom AI Models

21 時間

Deploying Fine-Tuned Models in Production

21 時間

Advanced Techniques in Transfer Learning

14 時間

Introduction to Transfer Learning

14 時間

Efficient Fine-Tuning with Low-Rank Adaptation (LoRA)

14 時間

Fine-Tuning Models and Large Language Models (LLMs)

14 時間

Fine-Tuning for Natural Language Processing (NLP)

21 時間

Last Updated: 2025-05-02

Upcoming Courses

Optimizing Large Models for Cost-Effective Fine-Tuning

2025-06-30 10:00

21 時間

Nagoya - Meieki Minami

¥ 683316 ~ (オンライン)

¥ 1366632 ~ (教室)

Introduction to Transfer Learning

2025-07-14 10:00

14 時間

Nagoya - Meieki Minami

¥ 455544 ~ (オンライン)

¥ 911088 ~ (教室)

Safety and Bias Mitigation in Fine-Tuned Models

2025-07-28 10:00

14 時間

Nagoya - Meieki Minami

¥ 455544 ~ (オンライン)

¥ 911088 ~ (教室)

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名古屋のFine-Tuningトレーニング

Nagoya - Meieki Minami

Explore Our Courses

Fine-Tuning Vision-Language Models (VLMs)

Safety and Bias Mitigation in Fine-Tuned Models

Fine-Tuning for Retrieval-Augmented Generation (RAG) Systems

Fine-Tuning Open-Source LLMs (LLaMA, Mistral, Qwen, etc.)

Parameter-Efficient Fine-Tuning (PEFT) Techniques for LLMs

Fine-Tuning Large Language Models Using QLoRA

Fine-Tuning with Reinforcement Learning from Human Feedback (RLHF)

Domain-Specific Fine-Tuning for Finance

Troubleshooting Fine-Tuning Challenges

Optimizing Large Models for Cost-Effective Fine-Tuning

Prompt Engineering and Few-Shot Fine-Tuning

Fine-Tuning Multimodal Models

Fine-Tuning DeepSeek LLM for Custom AI Models

Deploying Fine-Tuned Models in Production

Advanced Techniques in Transfer Learning

Introduction to Transfer Learning

Efficient Fine-Tuning with Low-Rank Adaptation (LoRA)

Fine-Tuning Models and Large Language Models (LLMs)

Fine-Tuning for Natural Language Processing (NLP)

Upcoming Courses

Optimizing Large Models for Cost-Effective Fine-Tuning

Introduction to Transfer Learning

Safety and Bias Mitigation in Fine-Tuned Models

This site in other countries/regions

Europe

Asia Pacific

North America

South America

Africa / Middle East

Other sites

名古屋のFine-Tuningトレーニング

Nagoya - Meieki Minami

Explore Our Courses

Fine-Tuning Vision-Language Models (VLMs)

Safety and Bias Mitigation in Fine-Tuned Models

Fine-Tuning for Retrieval-Augmented Generation (RAG) Systems

Fine-Tuning Open-Source LLMs (LLaMA, Mistral, Qwen, etc.)

Parameter-Efficient Fine-Tuning (PEFT) Techniques for LLMs

Fine-Tuning Large Language Models Using QLoRA

Fine-Tuning with Reinforcement Learning from Human Feedback (RLHF)

Domain-Specific Fine-Tuning for Finance

Troubleshooting Fine-Tuning Challenges

Optimizing Large Models for Cost-Effective Fine-Tuning

Prompt Engineering and Few-Shot Fine-Tuning

Fine-Tuning Multimodal Models

Fine-Tuning DeepSeek LLM for Custom AI Models

Deploying Fine-Tuned Models in Production

Advanced Techniques in Transfer Learning

Introduction to Transfer Learning

Efficient Fine-Tuning with Low-Rank Adaptation (LoRA)

Fine-Tuning Models and Large Language Models (LLMs)

Fine-Tuning for Natural Language Processing (NLP)

Upcoming Courses

Optimizing Large Models for Cost-Effective Fine-Tuning

Introduction to Transfer Learning

Safety and Bias Mitigation in Fine-Tuned Models

Other regions in 日本

Other Countries

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This site in other countries/regions

Europe

Asia Pacific

North America

South America

Africa / Middle East

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