ML Fundamentals

Lecture 8: Helicopter Aerodynamics

Lecture 2: Airplane Aerodynamics

Basics of Classes : Python Basics

Easy Way To Visualize Decision Tree- Machine Learning Algorithm

GOTO Episode 4

GOTO 2020 Climate Action Summit with keynote speaker Al Gore trailer

SVM from Scratch - Machine Learning Python (Support Vector Machine)

Automate Anomaly Detection Using Pycaret -Data Science And Machine Learning

Webinar: Admissions for University of North Texas Bachelor of Applied Arts and Sciences (B.A.A.S.)

5 websites to get Free Real-World Datasets for Data Science/ML Projects

Linear Regression Normal Equation Python

Jack Dorsey: Square, Cryptocurrency, and Artificial Intelligence | Lex Fridman Podcast #91

Webinar: Advising for the University of North Texas Bachelor of Applied Arts and Sciences Degree

MLOps meetup #7 Alex Spanos // TrueLayer 's MLOps Pipeline

Neural Networks from Scratch - P.3 The Dot Product

3rd wave of data scientists

Supervised Contrastive Learning

Intro to Deep Learning -- Student Presentations, Day 1 [Stat453, SS20]

Jack Clark — Building Trustworthy AI Systems

MA Model Code Example : Time Series Talk

50 Years of Computer Science: Professor Brailsford Q&A - Computerphile

[Rant] The Male Only History of Deep Learning

Python Tutorial: Fraud detection algorithms in action

Python Tutorial: Introduction to fraud detection

Lecture 14: Human Factors

Lecture 15: Flight Planning

Lecture 20: Flying at Night

Lecture 10: Communication and Flight Information

Lecture 19: Multi-Engine and Jets

Lecture 9: Meteorology

Lecture 11: Aircraft Ownership and Maintenance

Special Lecture: Oshkosh 2018

Who Is The Best Person To Judge You? Motivational Talks

Live Q&A Data Science

K-Nearest Neighbor from scratch - Machine Learning Python

The New Reality and Impact of COVID-19 on Higher Education Panel [2020 Coursera Virtual Conference]

Coursera for Campus: Supporting Universities During COVID-19 [2020 Coursera Virtual Conference]

Coursera Keynote from Jeff Maggioncalda, Coursera CEO [2020 Coursera Virtual Conference]

Step By Step Process To Learn Machine Learning Algorithm Efficiently

Lessons from Crisis Management: Rapid Innovation

Spam Classifier using Naive Bayes in Python

Naive Bayes from Scratch - Machine Learning Python

Reproducability flaws in end to end Machine Learning debugging

Standardization of Machine Learning tools like in Software Engineering with Venkata Pingali

Adjacent usecases and multistep feature engineering

Checkpointing, metadata, and confidence in your data

How many models in prod til I need a dedicated ML platform?

More difficult transition for data scientists to become ML engineers