Learning path · 3 parts
Machine Learning Fundamentals
by Gurpreet Deol · 3 parts · about 41 min · beginner
The ideas every later path relies on: data, models, loss, generalization and the workflow of a project.
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Articles
Machine Learning
Why Your Model Works in the Notebook and Fails in Production
A model that scores 95% accuracy in a Jupyter notebook can quietly fail once it is serving real traffic. Here …
The MLHub Posts Organization
4 hours ago • 14 min read
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0
5
Data Science
Ten Data Leakage Mistakes and How to Catch Them
A practical tour of the ten most common ways test information sneaks into model training, with worked examples and concrete …
The MLHub Posts Organization
2 days, 20 hours ago • 17 min read
0
0
25
Machine Learning
Accuracy Is Not Enough: Five Metrics Stories
Accuracy is the easiest metric to understand and one of the easiest to be fooled by. Five small, worked examples …
The MLHub Posts Organization
4 days, 20 hours ago • 14 min read
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0
38
Career Development
The Machine Learning Interview: What Is Really Asked
A practical breakdown of what machine learning interviews actually test, with worked examples covering coding, ML fundamentals, case studies, system …
2 weeks, 5 days ago • 21 min read
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49
Career Development
A 12-Month Study Plan for Machine Learning
A month-by-month roadmap for learning machine learning from first principles to a job-ready portfolio, with concrete projects, time budgets, and …
3 weeks, 3 days ago • 18 min read
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111
Machine Learning
Features, Labels and Datasets
A plain-language guide to the raw material of supervised learning: what rows, columns, features and labels actually are, with worked …
MLHub Academy Organization
by Gurpreet Deol • 3 weeks, 4 days ago • 15 min read
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0
30
Machine Learning
Supervised, Unsupervised and Reinforcement Learning
A plain-language tour of the three main ways a machine learning system can learn, with small worked examples showing what …
MLHub Academy Organization
by Gurpreet Deol • 3 weeks, 5 days ago • 13 min read
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84
Career Development
Data Scientist, ML Engineer or AI Engineer: What Each Role Does
A plain-language guide to what data scientists, machine learning engineers and AI engineers actually do day to day, with a …
3 weeks, 5 days ago • 17 min read
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0
68
Machine Learning
What Machine Learning Is, and What It Is Not
A plain-language introduction to machine learning that builds intuition with a worked example, gives a precise definition, and clears up …
MLHub Academy Organization
by Gurpreet Deol • 3 weeks, 6 days ago • 13 min read
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0
93
Data Science
Foundations of Probability, Sample Spaces, & Random Variables
Master the basics of probability for machine learning. Explore sample spaces, expected values, variance, and the Central Limit Theorem with …
The MLHub Posts Organization
1 month, 1 week ago • 7 min read
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0
25
Machine Learning
The Math Behind Modern AI, Derived and Then Coded in NumPy
The maths modern AI leans on, derived step by step and checked against clean NumPy. Dense layers, regression, cross-entropy gradients, …
1 month, 1 week ago • 53 min read
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Latest News
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