Category: Technology

Ingenuity’s Historic Flights on Mars

Ingenuity, NASA’s experimental helicopter, has been redefining the possibilities of flight on Mars since its arrival with the Perseverance rover in February 2021. Situated in the Jezero Crater, both the rover and the helicopter have been tirelessly collecting data and images, contributing to the search for signs of ancient life on the Red Planet.

 

In April 2021, Ingenuity achieved a monumental feat – becoming the first aircraft to perform a powered, controlled flight on another planet. Originally planned for just five flights, Ingenuity has exceeded all expectations, completing 66 flights to date. Each flight provides invaluable insights for future space-bound aircraft.

 

Travis Brown, Ingenuity’s chief engineer at NASA’s Jet Propulsion Laboratory (JPL), highlights the aircraft’s continuous evolution. Recently, Ingenuity has doubled its top speed and altitude records, enhancing both its operational efficiency and landing capabilities.

 

However, the flights are brief, typically spanning two to three minutes, due to energy and temperature constraints. The navigation system also limits the helicopter’s speed. To overcome this, the Ingenuity team has strategically increased the flight altitude, allowing for longer visual contact with surface markers for better navigation.

Machine Learning for Everybody

Kickstart your machine learning journey with “Machine Learning for Everybody,” led by Kylie Ying. This course adopts a hands-on, code-first approach, guiding you through the creation of fascinating machine learning models using Google Colab. You’ll engage in practical model-building while absorbing just enough theory to understand the underlying concepts. The course covers:

Introduction to Machine Learning

K-Nearest Neighbors

Naive Bayes

Logistic Regression

Linear Regression

K-Means Clustering

Principal Component Analysis (PCA)

Kaggle Machine Learning Courses

Kaggle, known for its real-world data challenges, offers a series of micro-courses that provide a solid foundation in machine learning. These courses, which can be completed in a few hours, include:

Intro to Machine Learning

Intermediate Machine Learning

Feature Engineering

These courses cover essential topics like model validation, underfitting and overfitting, random forests, handling missing values, ML pipelines, XGBoost, mutual information, and more.

Machine Learning in Python with Scikit-Learn

Offered on the FUN MOOC platform, this course is created by the core developers of scikit-learn. It comprehensively covers building machine learning models with scikit-learn, reinforced with video tutorials and Jupyter notebooks. Key areas include:

Predictive Modeling Pipeline

Model Performance Evaluation

Hyperparameter Tuning

Linear and Decision Tree Models

Ensemble Models

Machine Learning Crash Course by Google

This Google course is an excellent resource for learning machine learning with TensorFlow. It includes foundational concepts, engineering principles, and real-world system applications. The course covers:

ML Foundations

Introduction to TensorFlow

Feature Engineering

Neural Networks

Static vs. Dynamic Training and Inference

Data Dependencies and Fairness

CS229: Machine Learning by Stanford University

For those seeking a deeper, more technical understanding, Stanford University’s CS229 is unparalleled. It offers the depth of a semester-long university course, covering supervised and unsupervised learning, deep learning, regularization, and reinforcement learning.

This curated list of courses is designed to democratize knowledge in machine learning, proving that passion, dedication, and practical skills can pave the way for a successful career in this dynamic field. Whether for professional advancement or personal satisfaction, these resources are your gateway to mastering machine learning.