Published Oct 28, 2020

Kaggle, ML Community / Engineering (Sanyam Bhutani)

Insightful discussions with Sanyam Bhutani delve into the transformative power of content creation in AI learning, the dynamics of freelancing in machine learning, and the comparative value of formal and self-taught educational paths, while offering practical insights on the strategic use of Kaggle competitions in skill development.

Episode Highlights

Topics covered

Episode Highlights

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Dexa/Machine Learning Street Talk (MLST)

Kaggle, ML Community / Engineering (Sanyam Bhutani)

Topics covered

Popular Clips

Testing Machine Learning

Evolution of Machine Learning

Curiosity vs. Structure

Kaggle Practices

Feature Magnitudes

Automating Machine Learning

Model Interpretability

Content Creation Impact

Adversarial Attacks Complexity

Data Science Community Insights

Online Learning Accountability

Freelancing Tips

Enhancing Kaggle Competitions

Advanced Learning Resources

Episode Highlights

Content Creation

Freelancing in ML

Learning Pathways

Kaggle Practices

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Sayak Paul

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#046 The Great ML Stagnation (Mark Saroufim and Dr. Mathew Salvaris)

Jordan Edwards: ML Engineering and DevOps on AzureML

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#032- Simon Kornblith / GoogleAI - SimCLR and Paper Haul!

WelcomeAIOverlords (Zak Jost)

#035 Christmas Community Edition!

#97 SREEJAN KUMAR - Human Inductive Biases in Machines from Language

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Kaggle, ML Community / Engineering (Sanyam Bhutani)

Topics covered

Popular Clips

Episode Highlights

Content CreationSanyam Bhutani, a prominent figure in the AI community, discusses the pivotal role of content creation in learning and knowledge dissemination. He shares personal experiences and insights on how content creation bridges gaps in understanding complex AI concepts.

Content Creation

Freelancing in MLNext, Sanyam Bhutani shares his journey into freelancing in machine learning, offering practical advice and personal anecdotes. He discusses the importance of genuine connections and overcoming challenges in the field.

Freelancing in ML

Learning PathwaysThe discussion shifts to the comparison between formal education and self-taught methods in machine learning. Sanyam Bhutani and Tim Scarfe explore the evolving landscape of education, highlighting the role of community-driven learning and advanced resources.

Learning Pathways

Kaggle PracticesSanyam Bhutani shares insights on the practical benefits and challenges of participating in Kaggle competitions. He discusses how these experiences translate to real-world applications and the importance of advanced feature engineering techniques.

Kaggle Practices

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