Machine Learning A-Z : Become Kaggle Master
Machine Learning A-Z : Become Kaggle Master
.MP4, AVC, 1000 kbps, 1280x720 | English, AAC, 128 kbps, 2 Ch | 36h 19m | 13.97 GB
Created by Teclov Pvt Ltd
.MP4, AVC, 1000 kbps, 1280x720 | English, AAC, 128 kbps, 2 Ch | 36h 19m | 13.97 GB
Created by Teclov Pvt Ltd
Master Machine Learning Algorithms Using Python From Beginner to Super Advance Level including Mathematical Insights.
What you'll learn
Master Machine Learning on Python
Learn to use MatplotLib for Python Plotting
Learn to use Numpy and Pandas for Data Analysis
Learn to use Seaborn for Statistical Plots
Learn All the Mathmatics Required to understand Machine Learning Algorithms
Implement Machine Learning Algorithms along with Mathematic intutions
Projects of Kaggle Level are included with Complete Solutions
Learning End to End Data Science Solutions
All Advanced Level Machine Learning Algorithms and Techniques like Regularisations , Boosting , Bagging and many more included
Learn All Statistical concepts To Make You Ninza in Machine Learning
Real World Case Studies
Model Performance Metrics
Deep Learning
Model Selection
Want to become a good Data Scientist? Then this is a right course for you.
This course has been designed by IIT professionals who have mastered in Mathematics and Data Science. We will be covering complex theory, algorithms and coding libraries in a very simple way which can be easily grasped by any beginner as well.
We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science from beginner to advance level.
We have solved few Kaggle problems during this course and provided complete solutions so that students can easily compete in real world competition websites.
We have covered following topics in detail in this course:
1. Python Fundamentals
2. Numpy
3. Pandas
4. Some Fun with Maths
5. Inferential Statistics
6. Hypothesis Testing
7. Data Visualisation
8. EDA
9. Simple Linear Regression
10. Multiple Linear regression
11. Hotstar/ Netflix: Case Study
12. Gradient Descent
13. KNN
14. Model Performance Metrics
15. Model Selection
16. Naive Bayes
17. Logistic Regression
18. SVM
19. Decision Tree
20. Ensembles - Bagging / Boosting
21. Unsupervised Learning
22. Dimension Reduction
23. Advance ML Algorithms
24. Deep Learning
Who this course is for:
This course is meant for anyone who wants to become a Data Scientist
This course has been designed by IIT professionals who have mastered in Mathematics and Data Science. We will be covering complex theory, algorithms and coding libraries in a very simple way which can be easily grasped by any beginner as well.
We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science from beginner to advance level.
We have solved few Kaggle problems during this course and provided complete solutions so that students can easily compete in real world competition websites.
We have covered following topics in detail in this course:
1. Python Fundamentals
2. Numpy
3. Pandas
4. Some Fun with Maths
5. Inferential Statistics
6. Hypothesis Testing
7. Data Visualisation
8. EDA
9. Simple Linear Regression
10. Multiple Linear regression
11. Hotstar/ Netflix: Case Study
12. Gradient Descent
13. KNN
14. Model Performance Metrics
15. Model Selection
16. Naive Bayes
17. Logistic Regression
18. SVM
19. Decision Tree
20. Ensembles - Bagging / Boosting
21. Unsupervised Learning
22. Dimension Reduction
23. Advance ML Algorithms
24. Deep Learning
Who this course is for:
This course is meant for anyone who wants to become a Data Scientist
Machine Learning A-Z : Become Kaggle Master
Machine Learning A-Z : Become Kaggle Master
Machine Learning A-Z : Become Kaggle Master
