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Real World Machine Learning Project In Python From Scratch - OneDDL - 12-21-2023 Free Download Real World Machine Learning Project In Python From Scratch Published 12/2023 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.24 GB | Duration: 1h 7m Complete Real World Machine Learning Project In Python From Scratch What you'll learn Gain insights into the principles and applications of machine learning in real-world scenarios across various domains. Learn how to choose a machine learning project, define clear goals, and understand the business or problem context. Dive into feature engineering to enhance model performance by selecting, transforming, and creating relevant features. Learn how to build a predictive system, integrate your machine learning model, and deploy it for making real-world predictions. Requirements Basic understanding of Python programming. Access to a computer with Python installed. Description Course Title: Real World Machine Learning Project in Python From ScratchCourse Description:Welcome to the Real World Machine Learning Project in Python From Scratch course, an immersive experience that takes you through the entire lifecycle of building a practical machine learning project. Whether you're a novice curious about the end-to-end process or an intermediate learner eager to enhance your skills, this course is crafted to guide you through the complexities of real-world machine learning projects using Python.What You Will Learn:Introduction to Real-World Machine Learningelve into the principles and applications of machine learning in real-world scenarios, exploring its diverse applications across industries.Selecting a Project and Defining Goals:Learn how to choose a machine learning project, define clear goals, and understand the business or problem context for effective project planning.Data Collection and Exploration:Master techniques for collecting and preparing data, performing exploratory data analysis (EDA) to extract valuable insights essential for project success.Data Preprocessing and Cleaning:Understand the significance of data preprocessing and cleaning, and implement strategies to handle missing values, outliers, and other data anomalies.Feature Engineeringive into the world of feature engineering, enhancing model performance by selecting, transforming, and creating relevant features to drive better predictions.Choosing and Implementing Machine Learning Algorithms:Explore a variety of machine learning algorithms, gain the skills to select the most suitable ones for your project, and implement them using Python.Model Training and Evaluation:Grasp the process of training machine learning models, optimize hyperparameters, and evaluate model performance using industry-standard metrics.Hyperparameter Tuning and Model Optimizationive deep into hyperparameter tuning techniques and optimization strategies, ensuring your models are fine-tuned for efficiency and accuracy.Building a Predictive System:Learn the steps to build a predictive system, integrating your machine learning model and deploying it for making real-world predictions.Monitoring and Maintaining Models:Understand the importance of monitoring and maintaining machine learning models to ensure ongoing relevance and accuracy in dynamic environments.Ethical Considerations and Best Practices:Engage in meaningful discussions about ethical considerations in machine learning projects and adhere to best practices for responsible development.Why Enroll:Hands-On Project: Engage in a comprehensive hands-on project to reinforce your learning through practical application.Real-World Applications: Acquire skills applicable to real-world scenarios, enhancing your ability to create effective machine learning solutions.Community Support: Join a community of learners, share experiences, and seek assistance from instructors and peers throughout your learning journey.Embark on this practical learning adventure and become proficient in building a Real World Machine Learning Project in Python From Scratch. Enroll now and gain the skills to create impactful machine learning solutions! Overview Section 1: MACHINE LEARNING PROJECT ONE Lecture 1 INTRO TO FACIAL RECOGNITION USING TENSORFLOW PROJECT Lecture 2 DATASET CREATION FOR FACIAL RECOGNITION Lecture 3 TRAINING THE DATASET Lecture 4 VALIDTATE THE TRAINED MODEL Lecture 5 DOWNLOAD THE MODEL AND ITS FEATURES Lecture 6 EXTRACT THE MODEL AND ITS LABELS Lecture 7 INSTALL PACKAGE IN PYCHARM IDE Lecture 8 EXECUTE THE PROJECT IN PYCHARM IDE Section 2: INTRODUCTION TO SECOND PROJECT IN MACHINE LEARNING Lecture 9 INTRODUCTION TO OBJECT RECOGNITION AND ITS FEATURES Lecture 10 DATASET CREATION FOR PROJECT Lecture 11 TRAIN THE DATASET Lecture 12 VALIDATE THE TRAINED MODEL Lecture 13 DOWNLOAD MODEL Lecture 14 EXTRACT THE MODEL AND ITS FILES Lecture 15 PROJECT CODE EXPLANATION Lecture 16 PROJECT EXECUTE AND OUTPUT Beginners interested in understanding the end-to-end process of a machine learning project.,Intermediate learners seeking practical experience in building real-world machine learning systems.,Professionals aiming to apply machine learning in their work or projects. 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