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Description
Course Title: Real World Machine Learning Project in Python From Scratch
Course 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 Learning:
Delve 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 Engineering:
Dive 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 Optimization:
Dive 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!
| Total Students | 6609 |
|---|---|
| Original Price($) | |
| Sale Price | Free |
| Number of lectures | 16 |
| Number of quizzes | 0 |
| Total Reviews | 32 |
| Global Rating | 3.75 |
| Instructor Name | ARUNNACHALAM SHANMUGARAAJAN |
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