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TensorFlow Prediction: Identify Penguin Species
In this project, learners will gain the skill of building and evaluating machine learning models using TensorFlow Decision Forests to accurately classify penguin species based on physical measurements. They will construct a comprehensive machine learning model under the guidance of the instructor. Learners will master specific skills including data preprocessing and cleaning, feature selection and importance analysis, and model evaluation using performance metrics. These skills will enable learners to handle real-world data challenges effectively. The benefit of taking this project is that it provides practical, hands-on experience in applying machine learning techniques to a real-world dataset, enhancing learners' ability to develop accurate and reliable models for ecological and conservation purposes. This project is suitable for TensorFlow beginners with a decent Python background, including knowledge of classes, functions, and some experience with pandas or numpy. While conceptual knowledge related to decision trees and random forests would be helpful, it is not required.
Duration
8 Months
Institution
Coursera
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Coursera.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$120
Total Est. Investment
$120
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the TensorFlow Prediction: Identify Penguin Species program at Coursera are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.