DataMListic

Subscribers 52.2K

Videos 482

Views 5.4M

Channels Like DataMListic

DataMListic covers machine learning, AI, and data science concepts through explainer-style tutorials that break down topics like Bayesian methods, neural networks, optimization, and probabilistic modeling. The channel emphasizes explained and deep dive content, with a cadence that suggests regular uploads and an average of about 4.6K views per video across its 482 published videos since joining in 2020.

AI summary

Similar Channels

We found 49 YouTube channels similar to DataMListic

StatQuest with Josh Starmer YouTube channel thumbnail

#1

StatQuest with Josh Starmer view on YouTube ▶

86% relevance

Subscribers 1.6M

Videos 293

Views 89.3M

Appearances 17

SERP 100%

Similarity 76%

neural networks explained unsupervised learning methods gradient descent optimization

High search overlap on neural networks, gradient descent, and unsupervised learning aligns with DataMListic’s ML-focused audience, and the content similarity is strong (86% match) indicating closely resembling teaching style and topics.

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IBM Technology YouTube channel thumbnail

#2

IBM Technology view on YouTube ▶

66% relevance

Subscribers 1.6M

Videos 1.5K

Views 108.6M

Appearances 9

SERP 57%

Similarity 71%

machine learning basics supervised learning algorithms neural networks explained

Shares foundational ML topics like machine learning basics and neural networks; moderate search overlap but a distinct corporate/tech-news presentation yields a solid audience alignment with DataMListic’s ML explanations (66% match).

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#3

Stanford Online

62% relevance

Subscribers 1.1M

Videos 2.9K

Views 77.1M

Appearances 10

SERP 47%

Similarity 72%

optimization in ML statistical learning theory linear classifiers

Both address optimization, statistical learning theory, and linear classifiers, overlapping in depth and academic framing, resulting in a 62% match in audience queries and content.

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#4

3Blue1Brown view on YouTube ▶

60% relevance

Subscribers 8.2M

Videos 229

Views 727.0M

Appearances 6

SERP 34%

Similarity 77%

probability in ML neural networks explained gradient descent optimization

Overlap on probability and gradient descent in ML and a similar explanatory intent, with high content similarity (neural networks explained, gradient descent) but broader visual-math style driving a 60% match.

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Infinite Codes YouTube channel thumbnail

#5

Infinite Codes view on YouTube ▶

55% relevance

Subscribers 128K

Videos 40

Views 4.7M

Appearances 5

SERP 28%

Similarity 73%

machine learning basics supervised learning algorithms unsupervised learning methods

Covers ML basics and supervised/unsupervised methods much like DataMListic, yielding a 55% match that reflects comparable topic coverage though differing in channel scale and presentation.

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#6

Visually Explained

54% relevance

Subscribers 82K

Videos 31

Views 4.4M

Appearances 4

SERP 18%

Similarity 78%

optimization in ML gradient descent optimization

Shares emphasis on ML optimization and gradient descent, aligning with DataMListic’s tutorial approach, giving a 54% match driven by similar visual explanation style and topics.

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Content Landscape

Top competitors by match strength are StatQuest with Josh Starmer (86% match) and IBM Technology (66% match), followed by Stanford Online (62%), 3Blue1Brown (60%), and Infinite Codes (55%). They overlap with DataMListic on queries such as neural networks explained, gradient descent optimization, and machine learning basics. DataMListic has 52.2K subscribers, while StatQuest and IBM Technology each have about 1.6M subscribers, Stanford Online has around 1.1M, 3Blue1Brown about 8.2M, and Infinite Codes about 128K, highlighting a wide range in audience size among competitors. The overlapping queries include machine learning basics, optimization in ML, neural networks explained, and supervised/unsupervised learning methods, indicating direct competition for similar educational ML/search content.

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Video Highlights

Didn't Make the Cut

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#16	50%	Andrew Gordon Wilson	78%	2.4K	6%	1
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#25	47%	Udacity	67%	646K	19%	3
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#29	47%	Kylie Ying	75%	89.8K	5%	1
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Search Queries Used

machine learning basics probability in ML optimization in ML statistical learning theory supervised learning algorithms neural networks explained unsupervised learning methods probabilistic modeling gradient descent optimization Bayesian methods clustering algorithms linear classifiers dimensionality reduction model evaluation metrics probability distributions explained regularization techniques overfitting prevention cross validation methods transfer learning basics reinforcement learning fundamentals

Frequently Asked Questions

Which YouTube channels are most similar to DataMListic?

DataMListic's biggest competitors on YouTube are StatQuest with Josh Starmer (86% match, 1.6M subscribers), IBM Technology (66% match, 1.6M subscribers), and Stanford Online (62% match, 1.1M subscribers). All three channels share a focus on explaining and teaching data science, machine learning, and related concepts, matching DataMListic's keywords like machine learning, ai, and data science.

What type of content does DataMListic make?

DataMListic creates educational videos explaining machine learning and data science concepts, as shown by titles like Bayesian Optimization, Softmax function - Explained, Convolutional Neural Networks - Explained, Maximum Likelihood - Explained, and K-Means - Explained. The channel averages about 4.6K views per video, with about 52.2K subscribers listed, and uploads occur with some regularity (average views per video about 4.6K).

How do we determine which channels are similar to DataMListic?

We analyze DataMListic'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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