Complete Machine Learning Course With Python
Chaitanya attaluri
11:54:05
Description
Learn to create Machine Learning Algorithms in Python using Different Datasets
What You'll Learn?
- Around 15+ Machine learning algorithms explanation with different datasets and 15+ assignment for practice
- Supervised and Unsupervised learning models,PRINCIPLE COMPONENT ANALYSIS(PCA)
- Solve any problem in your business, job or personal life with powerful Machine Learning models
- Train machine learning algorithms to predict house prices, identify handwriting, detect cancer cells & more
Who is this for?
What You Need to Know?
More details
DescriptionThis course provides a broad introduction to machine learning and statistical pattern recognition.
Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins);
Gain complete machine learning tool sets to tackle most real world problems
Understand the various regression, classification and other ml algorithms performance metrics such as R-squared, MSE, accuracy, confusion matrix,etc. and when to use them.
Combine multiple models with by bagging, boosting or stacking
Make use to unsupervised Machine Learning (ML) algorithms such as Hierarchical clustering, k-means clustering etc. to understand your data
Develop in Spyder and various IDE
Communicate visually and effectively with Matplotlib and Seaborn
Engineer new features to improve algorithm predictions
Make use of train/test, K-fold and Stratified K-fold cross validation to select correct model and predict model perform with unseen data
Use SVM for handwriting recognition, and classification problems in general
Use decision trees to predict staff attrition
And much much more!
No Machine Learning required. Although having some basic Python experience would be helpful, no prior Python knowledge is necessary as all the codes will be provided and the instructor will be going through them line-by-line and you get friendly support in the Q&A area.
If you want to ride the machine learning wave and enjoy the salaries that data scientists make, then this is the course for you!
Take this course and become a machine learning engineer!
Who this course is for:
- Anyone willing and interested to learn machine learning algorithm with Python
- Anyone who want to choose carrer in Datascience,AI,Machine learning,Data analytics
- Anyone wishes to move beyond the basics and develop an understanding of the whole range of machine learning algorithms
This course provides a broad introduction to machine learning and statistical pattern recognition.
Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins);
Gain complete machine learning tool sets to tackle most real world problems
Understand the various regression, classification and other ml algorithms performance metrics such as R-squared, MSE, accuracy, confusion matrix,etc. and when to use them.
Combine multiple models with by bagging, boosting or stacking
Make use to unsupervised Machine Learning (ML) algorithms such as Hierarchical clustering, k-means clustering etc. to understand your data
Develop in Spyder and various IDE
Communicate visually and effectively with Matplotlib and Seaborn
Engineer new features to improve algorithm predictions
Make use of train/test, K-fold and Stratified K-fold cross validation to select correct model and predict model perform with unseen data
Use SVM for handwriting recognition, and classification problems in general
Use decision trees to predict staff attrition
And much much more!
No Machine Learning required. Although having some basic Python experience would be helpful, no prior Python knowledge is necessary as all the codes will be provided and the instructor will be going through them line-by-line and you get friendly support in the Q&A area.
If you want to ride the machine learning wave and enjoy the salaries that data scientists make, then this is the course for you!
Take this course and become a machine learning engineer!
Who this course is for:
- Anyone willing and interested to learn machine learning algorithm with Python
- Anyone who want to choose carrer in Datascience,AI,Machine learning,Data analytics
- Anyone wishes to move beyond the basics and develop an understanding of the whole range of machine learning algorithms
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Chaitanya attaluri
Instructor's Courses
Udemy
View courses Udemy- language english
- Training sessions 59
- duration 11:54:05
- Release Date 2024/06/22
