Daniel Bourke

Subscribers 249K

Videos 346

Views 12.5M

Channels Like Daniel Bourke

Daniel Bourke presents machine learning and AI-focused content with emphasis on on-device and edge AI topics, LLM fine-tuning, multimodal retrieval, and health-related applications. His videos feature tutorials and deep-dives on Python, PyTorch, TensorFlow, and practical ML workflows, often tied to health monitoring and skin health tracking. The channel, active since 2016, publishes a mix of long-form tutorials and walkthroughs, with an average view count around 135.8K per video across 346 uploads, and a recent video lineup including roadmaps, fine-tuning tutorials, and end-to-end pipelines.

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Similar Channels

We found 48 YouTube channels similar to Daniel Bourke

IBM Technology YouTube channel thumbnail

#1

IBM Technology view on YouTube ▶

88% relevance

Subscribers 1.6M

Videos 1.5K

Views 108.6M

Appearances 28

SERP 100%

Similarity 80%

small language models LLM fine-tuning multimodal retrieval

High search overlap on small language models and LLM fine-tuning (100% search overlap) with content focused on technical AI topics (80% content overlap), aligning with Daniel Bourke's audience interested in practical AI techniques and model customization.

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#2

Tina Huang view on YouTube ▶

55% relevance

Subscribers 1.1M

Videos 321

Views 49.6M

Appearances 3

SERP 16%

Similarity 81%

open source AI models prompt engineering vs context engineering

Shares audience interest in open source AI models and prompt engineering vs context engineering (low search overlap 16%) but high content similarity (81%), indicating similar topics and explanations while appealing to a different search intent or discovery path.

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#3

Stanford Online

53% relevance

Subscribers 1.1M

Videos 2.9K

Views 77.1M

Appearances 3

SERP 11%

Similarity 82%

self supervised learning personalized health tech

Overlap exists in topics like self-supervised learning and health tech hints (search 11%), with strong content alignment (82%), suggesting a shared interest area in advanced AI concepts thoughStanford Online emphasizes formal courses.

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freeCodeCamp.org YouTube channel thumbnail

#4

freeCodeCamp.org view on YouTube ▶

53% relevance

Subscribers 11.5M

Videos 2.1K

Views 954.1M

Appearances 2

SERP 14%

Similarity 79%

LLM fine-tuning

Significant audience overlap around LLM fine-tuning (search 14%), with high content similarity (79%), meaning both channels cover practical AI tutorial content despite different presentation styles.

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#5

codebasics

53% relevance

Subscribers 1.5M

Videos 1.1K

Views 153.6M

Appearances 10

SERP 17%

Similarity 77%

LLM fine-tuning edge AI inference prompt engineering vs context engineering

Similar focus on LLM fine-tuning and prompt engineering vs context engineering (search 17%), plus strong content alignment (77%), indicating parallel tutorial content with a slightly broader emphasis on edge AI topics.

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#6

Google Cloud Tech

53% relevance

Subscribers 1.4M

Videos 2K

Views 53.4M

Appearances 5

SERP 16%

Similarity 77%

on-device AI multimodal retrieval prompt engineering vs context engineering

Shared topics on on-device AI and multimodal retrieval (search 16%), and prompt vs context engineering (77% content), pointing to comparable AI deployment and optimization content at enterprise scale.

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Content Landscape

Discovered competitors include IBM Technology (88% match) and Tina Huang (55% match) as top contenders. IBM Technology and Tina Huang share overlapping queries with Daniel Bourke around small language models, LLM fine-tuning, open-source AI models, and prompt vs context engineering. Stanford Online (53% match) and freeCodeCamp.org (53% match) also align on related topics like self-supervised learning and LLM fine-tuning, with freeCodeCamp.org having a substantially larger subscriber base. Codebasics (53% match) also overlaps on LLM fine-tuning, edge AI inference, and prompt engineering vs context engineering. Daniel Bourke has 249K subscribers, significantly fewer than IBM Technology (1.6M), freeCodeCamp.org (11.5M), and the others, highlighting a competitive landscape where the channel competes for similar search queries but from a comparatively smaller audience.

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Video Highlights

Didn't Make the Cut

42 additional channels that were close

Rank	Relevance	Channel	Similarity	Subscribers	SERP	Appearances
#7	52%	Edge Impulse	73%	17.2K	21%	6
#8	52%	Eye on Tech ▶	77%	128K	13%	4
#9	52%	Andy Stapleton ▶	74%	363K	18%	4
#10	51%	Hey AI	77%	37.8K	13%	2
#11	51%	DeepLearningAI	80%	664K	9%	3
#12	51%	Alex Ziskind ▶	75%	462K	16%	6
#13	50%	AssemblyAI	79%	180K	7%	1
#14	50%	NVIDIA ▶	78%	2.2M	9%	3
#15	50%	Qualcomm Developer	76%	33.7K	10%	3
#16	50%	Boris Meinardus	78%	96.9K	7%	1
#17	49%	TFiR	78%	30.1K	7%	3
#18	49%	Tech With Tim ▶	76%	2.0M	9%	5
#19	48%	Tech Advent	75%	35.1K	9%	1
#20	48%	GPU MODE	74%	32.7K	10%	3
#21	48%	Programming with Mosh ▶	75%	5.0M	9%	1
#22	48%	Egor Howell ▶	76%	67.7K	7%	2
#23	48%	Vinh Nguyen	74%	1.2K	9%	1
#24	47%	National Library of Medicine ▶	74%	168K	7%	1
#25	47%	Mickey Mellen	73%	4.5K	9%	1
#26	47%	Fireship ▶	74%	4.1M	7%	5
#27	47%	Spencer Scott Pugh ▶	73%	45.2K	9%	3
#28	47%	Salesforce ▶	73%	864K	9%	1
#29	47%	3Blue1Brown ▶	72%	8.2M	9%	4
#30	46%	Trends Place	73%	3.1K	7%	1
#31	46%	Android Developers ▶	72%	1.4M	9%	6
#32	46%	mlau	70%	35.5K	10%	8
#33	46%	TEDx Talks ▶	67%	44.2M	15%	6
#34	46%	HLTH	72%	2.5K	7%	1
#35	46%	Bloomberg Media Studios	70%	9.9K	9%	1
#36	45%	Lex Fridman ▶	71%	5.0M	7%	1
#37	45%	Data Wizardry ▶	65%	21.4K	16%	6
#38	44%	Vizuara	69%	212K	6%	4
#39	44%	LinuxDays	67%	3.4K	9%	1
#40	43%	Curbal	68%	148K	7%	1
#41	43%	Howon Noh ▶	66%	45.4K	9%	1
#42	43%	ElectricMoves	67%	54.6K	7%	1
#43	43%	Online Tech Tips	67%	33K	7%	1
#44	42%	Philips Healthcare ▶	66%	113K	8%	2
#45	42%	The Career Force	66%	71.9K	7%	1
#46	41%	Mobile Legends: Bang Bang	64%	17.7M	8%	3
#47	40%	Lex Clips	62%	1.6M	8%	3
#48	39%	CodeLucky ▶	61%	7.4K	6%	2

Search Queries Used

machine learning roadmap small language models on-device AI LLM fine-tuning multimodal retrieval vision language model health monitoring apps skin health tracking edge AI inference open source AI models LLM training playbook prompt engineering vs context engineering AI monthly insights neural network training on dgx ai hardware comparison on device AI basics edge AI deployment tiny models overview memory efficient models academic AI papers summary self supervised learning multimodal training tips mobile ML optimization privacy preserving ML model compression techniques health data analytics predictive health models clinical decision support explainable AI health personalized health tech neural nets efficiency hardware accelerated ML AI for wearables health data standards on device inference benchmarks

Frequently Asked Questions

Which YouTube channels are most similar to Daniel Bourke?

IBM Technology (match 88%, 1.6M subscribers), Tina Huang (match 55%, 1.1M subscribers), and Stanford Online (match 53%, 1.1M subscribers) are Daniel Bourke's biggest YouTube competitors. They share a focus on technology and education, including topics like artificial intelligence and machine learning, similar to Bourke's channel.

What type of content does Daniel Bourke make?

Daniel Bourke creates educational content about machine learning, AI, Python programming, and related tools, as indicated by video titles such as '2020 Machine Learning Roadmap', 'Small Language Models Are the Future: Fine-Tuning AI That Runs on Your iPhone', and 'Local Multimodal RAG Pipeline End-to-End Tutorial'. His channel appears to have frequent uploads with an average view count of around 135.8K per video, though the exact weekly upload frequency is not specified.

How do we determine which channels are similar to Daniel Bourke?

We analyze Daniel Bourke's recent videos, generate topic-relevant search queries, check YouTube search results, and compare the meaning of each channel's content to measure similarity. The result is a ranked list sorted by SERP overlap, semantic similarity, and search appearances.

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