gs gs125 video lectures

gs gs125 - Machine Learning Video Lectures The book/course code gs gs125 Machine Learning belongs to gs organization and contains 22 in total video lectures. The students of Gegasoft organiztion can watch these video lecture on NVAEducation. These videos are also availble on Youtube and students can watch these video lectures of Machine Learning on Youtube, however, NVAEducation facilitates students to be able to download these video lectures without using any VPS or third-party tool.

List of video lectures of gs gs125

Here bellow is a list of 22 video lectures related to the course gs gs125 Machine Learning of organization Gegasoft (gs). To play a lecture choose a lecture from the list bellow.

Video Lectures of gs125 Machine Learning

gs125 Machine Learning #1 - What is Machine Learning?

#1 - What is Machine Learning?

gs125 Machine Learning

gs125 Machine Learning #2 - Linear Regression Single Variable

#2 - Linear Regression Single Variable

gs125 Machine Learning

gs125 Machine Learning #3 - Linear Regression Multiple Variables

#3 - Linear Regression Multiple Variables

gs125 Machine Learning

gs125 Machine Learning #4 - Gradient Descent and Cost Function

#4 - Gradient Descent and Cost Function

gs125 Machine Learning

gs125 Machine Learning #5 - Save Model Using Joblib And Pickle

#5 - Save Model Using Joblib And Pickle

gs125 Machine Learning

gs125 Machine Learning #6 - Dummy Variables & One Hot Encoding

#6 - Dummy Variables & One Hot Encoding

gs125 Machine Learning

gs125 Machine Learning #7 - Training and Testing Data

#7 - Training and Testing Data

gs125 Machine Learning

gs125 Machine Learning #8 - Logistic Regression (Binary Classification)

#8 - Logistic Regression (Binary Classification)

gs125 Machine Learning

gs125 Machine Learning #9 - Logistic Regression (Multiclass Classification)

#9 - Logistic Regression (Multiclass Classification)

gs125 Machine Learning

gs125 Machine Learning #10 - Decision Tree

#10 - Decision Tree

gs125 Machine Learning

gs125 Machine Learning #11 - Support Vector Machine (SVM)

#11 - Support Vector Machine (SVM)

gs125 Machine Learning

gs125 Machine Learning #12 - Random Forest

#12 - Random Forest

gs125 Machine Learning

gs125 Machine Learning #13 - K Fold Cross Validation

#13 - K Fold Cross Validation

gs125 Machine Learning

gs125 Machine Learning #14 - K Means Clustering Algorithm

#14 - K Means Clustering Algorithm

gs125 Machine Learning

gs125 Machine Learning #15 - Naive Bayes Classifier Algorithm Part 1

#15 - Naive Bayes Classifier Algorithm Part 1

gs125 Machine Learning

gs125 Machine Learning #16 - Naive Bayes Classifier Algorithm Part 2

#16 - Naive Bayes Classifier Algorithm Part 2

gs125 Machine Learning

gs125 Machine Learning #17 - Hyper parameter Tuning (GridSearchCV)

#17 - Hyper parameter Tuning (GridSearchCV)

gs125 Machine Learning

gs125 Machine Learning #18 - L1 and L2 Regularization | Lasso, Ridge Regression

#18 - L1 and L2 Regularization | Lasso, Ridge Regression

gs125 Machine Learning

gs125 Machine Learning #19 - K nearest neighbors classification with python code

#19 - K nearest neighbors classification with python code

gs125 Machine Learning

gs125 Machine Learning #20 - Principal Component Analysis (PCA) with Python Code

#20 - Principal Component Analysis (PCA) with Python Code

gs125 Machine Learning

gs125 Machine Learning #21 - Bias vs Variance In Machine Learning

#21 - Bias vs Variance In Machine Learning

gs125 Machine Learning

gs125 Machine Learning #22 - Ensemble Learning - Bagging

#22 - Ensemble Learning - Bagging

gs125 Machine Learning

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