Regularization is the process of shrinking or regularising the coefficients towards zero in machine learning. To put it another way, regularisation prevents overfitting by discouraging the learning of a more complicated or flexible model.
The goal of optimising an objective function is to identify a set of inputs that results in a maximum or minimal function evaluation. Many machine learning algorithms, from fitting logistic regression models to training artificial neural networks, are based on this difficult topic.
One of the most fundamental topics in machine learning is regularisation. It's a method of preventing the model from overfitting by providing additional data. When using training data, the machine learning model may perform well, but when using test data, it may not.
Regularization Techniques in Deep Learning = minimises or eliminates the problem of overfitting. Keras-Tuner optimises neural network structures by reducing the number of connections and neurons for best performance.
When fitting a machine learning algorithm, function optimization is the reason for minimising error, cost, or loss. In a predictive modelling project, optimization is also done during data preparation, hyperparameter tweaking, and model selection.
Learner's Ratings
4.4
Overall Rating
69%
10%
13%
5%
3%
Reviews
M
Muhammad Qasim
5
Hi Kushal ! Your way of teaching is extremely helpful and you are one of the best teacher in the world.
Extremely helpful and I recommend to my peer as well for this course.
S
Shafi Akhtar
5
None
A
Aniket Kumar prasad
5
Very helpful and easy to understand all the concepts, best teacher for learning ML.
R
Rishu Shrivastav
5
explained everything in detail. I have a question learnvern provide dataset , and ppt ? or not?
V
VIKAS CHOUBEY
5
very nicely explained
V
Vrushali Kandesar
5
Awesome and very nicely explained!!!
One importing thing to notify to team is by mistakenly navie's practical has been added under svm lecture and vice versa (Learning Practical 1)
M
Mohd Mushraf
5
Amazing Teaching
J
Juboraj Juboraj
5
Easy to understand & explain details.
J
Joydeb
5
Awesome Course sir and your teaching style is very GOOD.
S
Shaga Chandrakanth Goud
5
Hi Kushal ji, Thanks a lot for a very good explanation. I have doubts about where we can get the dataset that you explained in the video. Can you make it available in resource ,so that we can downld
Share a personalized message with your friends.