June 2021
Day 60 – Support Vector Machines(SVM)
In our previous, we have gone through few models Linear Regression Model, Decision Tree Model, Random Forest Model, etc. Today, In this blog, we will see what a Support Vector Machine(SVM) is. Support Vector Machine is one ...
Day 59 – Predicting Fibonacci Sequence Numbers Using Neural Networks
Fibonacci Sequence patterns are inevitable in life, and we can see them in flowers, plants, seashells, etc. Today, we will see how to predict Fibonacci sequence using simple neural networks using the Tensorflow Keras library. Fibonacci ...
Day 58 – What is Perceptron Algorithm?
If you want to take a particular decision on a given task, for example, if a bank wants to approve a credit card for a person, they check a certain number of criteria to approve or deny. ...
Day 57 – Underfitting, Overfitting, and Regularization
Underfitting We have created a model, and you tested in training data, and the model provides the worst result. So the model is too simple and unable to predict the outputs based on the inputs. How to ...
Day 56 – No Free Lunch Theorem(NFL) in Artificial Intelligence/Machine Learning
You have created a model for a problem in Artificial Intelligence/Machine Learning that works perfectly and achieves 90 to 95% accuracy. Again, you take the same model and implement it in another problem; you found that it ...
Day – 46 – Mean Square Error(MSE), Root Mean Square Error(RMSE), Mean Absolute Error(MAE)
The linear regression problems use few performance measures Mean Square Error(MSE), Root Mean Square Error(RMSE), and Mean Absolute Error(MAE). Mean Square Error(MSE) Formula: Root Mean Square Error(RMSE) Formula: Mean Absolute Error(MAE) Formula: ...