- Coding for Machine Learning Algorithms in Python with Variety of datasets.
- New
- Rating: 5.0 out of 55.0 (4 ratings)
- 608 students
- 50min of on-demand video
- Created by Naman Singhal
- English
What you’ll learn
- Machine Learning Algorithms
- Coding
- Supervised Learning & Unsupervised Learning
- Data Visualization and Data Preprocessing
Requirements
- Maths behind Machine Learning
Description
Unlock the full potential of machine learning with our comprehensive Advanced Machine Learning Coding in Python course. Designed for both beginners and experienced developers, this course will take you on a deep dive into the world of machine learning and equip you with the skills and knowledge needed to excel in this rapidly evolving field.
In this hands-on course, you’ll embark on a journey that starts with the fundamentals of machine learning and gradually progresses to advanced techniques and real-world applications. You will gain proficiency in Python, the primary programming language of choice for machine learning, and learn how to harness powerful libraries such as sci-kit-learn to build and train complex models.
I will guide you through a structured curriculum that covers topics like data preprocessing, feature engineering, model selection, hyperparameter tuning, and deploying machine learning models. You’ll work on practical exercises, projects, and case studies, applying your newfound skills to solve real-world problems.
By the end of this course, you’ll be well-prepared to tackle the most challenging machine-learning tasks, from image and text classification to regression and reinforcement learning. Whether you’re aiming to advance your career, enhance your data analysis skills, or develop innovative machine-learning applications, this course provides the foundation you need. Join us and become a proficient machine-learning practitioner in Python!
Who this course is for:
- Beginners in Machine Learning Coding
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Course content
2 sections • 8 lectures • 50m total lengthCollapse all sections
Supervised Learning7 lectures • 45min
- Linear Regression10:20
- Logistic Regression06:47
- Ridge and Lasso Regression06:09
- Decision Tree Classifier04:48
- Decision Tree Regressor06:41
- Random Forest Classifier06:25
- XGBOOST Classifier03:43
Unsupervised Learning1 lecture • 5min
- Kmeans, DBSCAN and PCA Clustering Algorithms05:27
