5 Days 5 Machine Learning Projects From Scratch




What you'll learn
Understand the foundations of machine learning through hands-on projects.
Learn the end-to-end workflow of a machine learning project, from data preparation to model deployment.
Gain experience with popular machine learning libraries like scikit-learn, TensorFlow, and Pandas.
Explore diverse domains such as regression, classification, NLP, computer vision, and recommendation systems.
Requirements
Basic Python & Machine Learning Required
Description
Welcome to the "5 Days 5 Machine Learning Projects From Scratch" course, a fast-paced, hands-on learning experience designed to take you from theory to practice in just five days! This course is perfect for aspiring data scientists, machine learning enthusiasts, and professionals who want to enhance their portfolio with real-world projects.Each day focuses on building a fully functional machine learning project from scratch, covering various domains and techniques to give you a well-rounded experience. By the end of this course, you'll have completed five diverse projects, gaining invaluable skills in data preprocessing, model building, evaluation, and deployment. This course emphasizes practical skills, critical thinking, and hands-on implementation to ensure you're job-ready.What You'll Build:Day 1: Create Project Using Natural Language Processing.Day 2: Create Project Using logistic regression and neural networks.Day 3: Create Project Using Naive Bayes classification.Day 4: Create Project Using Medical Image Prediction.Day 5: Create Project For Ad Click Through Prediction.Whether you're a student, professional, or self-taught learner, this course equips you with the knowledge and confidence to tackle real-world machine learning problems. Acquire skills to confidently implement machine learning solutions in real-world scenarios. Start your journey today and transform your passion for machine learning into tangible expertise!
Overview
Section 1: Introduction To Resume Analyzer Project For Machine Learning Job
Lecture 1 Introduction To Project
Lecture 2 Resume Class 1 : Import Packages
Lecture 3 Resume Class 2 : Import Dataset
Lecture 4 Resume Class 3 : Extract Text From Resume
Lecture 5 Resume Class 4 : Tokenization
Lecture 6 Resume Class 5 : Match Keywords & Skills
Lecture 7 Resume Class 6 : Analyze Resume Score & Conclusion
Section 2: Ecommerce Product Category Classification Using Machine Learning
Lecture 8 Introduction To Project
Lecture 9 Ecommerce Class 1 : Import Packages
Lecture 10 Ecommerce Class 2 : Import Dataset
Lecture 11 Ecommerce Class 3 : Data Preprocessing
Lecture 12 Ecommerce Class 4 : Train Dataset Using Logistic Regression
Lecture 13 Ecommerce Class 5 : Output & Conclusion
Section 3: Emotion Detection From Text Using Natural Language Processing
Lecture 14 Introduction To Project
Lecture 15 Emotion Class 1 : Import Packages
Lecture 16 Emotion Class 2 : Import Dataset
Lecture 17 Emotion Class 3 : Dataset Preprocessing
Lecture 18 Emotion Class 4 : Train Dataset Using Naive Bayes
Lecture 19 Emotion Class 5 : Output & Conclusion
Section 4: AD Click Prediction Project Using Machine Learning
Lecture 20 Introduction To Project
Lecture 21 AD Class 1 : Import Packages
Lecture 22 AD Class 2 : Import Dataset
Lecture 23 AD Class 3 : Dataset Preprocessing
Lecture 24 AD Class 4 : Train Dataset Using Regression
Lecture 25 AD Class 5 : Output & Conclusion
Section 5: Diabetes Prediction Project Using Machine Learning
Lecture 26 Introduction To Project
Lecture 27 Diabetes Class 1 : Import Packages
Lecture 28 Diabetes Class 2 : Import Dataset
Lecture 29 Diabetes Class 3 : Data Preprocessing
Lecture 30 Diabetes Class 4 : Train Dataset
Lecture 31 Diabetes Class 5 : Output & Conclusion
Students,Python & Machine Learning Coders


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