Top Machine Learning Interview Questions :
(A Thread 🧵)
-------------------------------------------------------------------------------
#100DaysOfCode
#DEVCommunity
#Python
#Python3
(A Thread 🧵)
-------------------------------------------------------------------------------
#100DaysOfCode
#DEVCommunity
#Python
#Python3
Q) What is ‘Overfitting’ in Machine learning?
when a model describes noise instead of an underlying relationship, ‘overfitting’ occurs.
When a model is excessively complex, overfitting is normally observed, due to too many parameters with respect to the training data types.
when a model describes noise instead of an underlying relationship, ‘overfitting’ occurs.
When a model is excessively complex, overfitting is normally observed, due to too many parameters with respect to the training data types.
Q) How can you avoid overfitting?
-By using a lot of data overfitting can be avoided.
-if the Database is small, use "cross-validation". Here, the dataset splits into two: testing and training datasets :
Testing -> Tests model
Training -> Using datapoints
-By using a lot of data overfitting can be avoided.
-if the Database is small, use "cross-validation". Here, the dataset splits into two: testing and training datasets :
Testing -> Tests model
Training -> Using datapoints
Q) What is inductive machine learning?
The inductive machine learning involves the process of learning by examples, where a system, from a
set of observed instances tries to induce a general rule.
The inductive machine learning involves the process of learning by examples, where a system, from a
set of observed instances tries to induce a general rule.
Q) What are the five popular algorithms of Machine Learning?
- Probabilistic networks
- K-Nearest Neighbor
- Support vector machines (SVM)
- Neural Networks
- Decision Trees
- Probabilistic networks
- K-Nearest Neighbor
- Support vector machines (SVM)
- Neural Networks
- Decision Trees
Q) What is algorithm independent machine learning?
Machine learning in where mathematical foundations are independent of any particular classifier or a learning algorithm is referred to as algorithm independent machine learning.
#ArtificialIntelligence
Machine learning in where mathematical foundations are independent of any particular classifier or a learning algorithm is referred to as algorithm independent machine learning.
#ArtificialIntelligence
Q) What are the advantages of Naive Bayes?
In Naïve Bayes classifier will converge quicker than discriminative models like logistic regression, so
you need less training data. The main advantage is that it can’t learn the interactions between features.
In Naïve Bayes classifier will converge quicker than discriminative models like logistic regression, so
you need less training data. The main advantage is that it can’t learn the interactions between features.
Q) What are the two methods used for the calibration in Supervised Learning?
- Platt Calibration
- Isotonic Regression
These methods are designed for binary classification.
- Platt Calibration
- Isotonic Regression
These methods are designed for binary classification.
Q) Which method is frequently used to prevent overfitting?
When there is sufficient data ‘Isotonic Regression’ is used to prevent an overfitting issue.
When there is sufficient data ‘Isotonic Regression’ is used to prevent an overfitting issue.
Q) What are the two classification methods that SVM can
handle?
- Combining binary classifiers
- Modifying binary to incorporate multiclass learning
handle?
- Combining binary classifiers
- Modifying binary to incorporate multiclass learning
Q) What is PCA, KPCA, and ICA used for?
- PCA (Principal Components Analysis)
- KPCA ( Kernel based Principal Component Analysis)
- ICA (Independent Component Analysis)
These are feature extraction techniques used for dimensionality reduction.
- PCA (Principal Components Analysis)
- KPCA ( Kernel based Principal Component Analysis)
- ICA (Independent Component Analysis)
These are feature extraction techniques used for dimensionality reduction.
• • •
Missing some Tweet in this thread? You can try to
force a refresh
