Machine Learning Tutorial

Machine Learning Tutorial Machine Learning Life Cycle Python Anaconda setup Difference between ML/ AI/ Deep Learning Understanding different types of Machine Learning Data Pre-processing Supervised Machine Learning

ML Regression Algorithm

Linear Regression

ML Classification Algorithm

Introduction to ML Classification Algorithm Logistic Regression Support Vector Machine Decision Tree Naïve Bayes Random Forest

ML Clustering Algorithm

Introduction to ML Clustering Algorithm K-means Clustering Hierarchical Clustering

ML Association Rule learning Algorithm

Introduction to association Rule Learning Algorithm

How To

How to Learn AI and Machine Learning How Many Types of Learning are available in Machine Learning How to Create a Chabot in Python Using Machine Learning

ML Questions

What is Cross Compiler What is Artificial Intelligence And Machine Learning What is Gradient Descent in Machine Learning What is Backpropagation in a Neural Network Why is Machine Learning Important What Machine Learning Technique Helps in Answering the Question Is Data Science and Machine Learning Same

Differences

Difference between Machine Learning and Deep Learning Difference between Machine learning and Human Learning

Miscellaneous

Top 5 programming languages and their libraries for Machine Learning Basics Vectors in Linear Algebra in ML Decision Tree Algorithm in Machine Learning Bias and Variances in Machine Learning Machine Learning Projects for the Final Year Students Top Machine Learning Jobs Machine Learning Engineer Salary in Different Organisation Best Python Libraries for Machine Learning Regularization in Machine Learning Some Innovative Project Ideas in Machine Learning Decoding in Communication Process Working of ARP Hands-on Machine Learning with Scikit-Learn, TensorFlow, and Keras Kaggle Machine Learning Project Machine Learning Gesture Recognition Machine Learning IDE Pattern Recognition and Machine Learning a MATLAB Companion Chi-Square Test in Machine Learning Heart Disease Prediction Using Machine Learning Machine Learning and Neural Networks Machine Learning for Audio Classification Standardization in Machine Learning Student Performance Prediction Using Machine Learning Automated Machine Learning Hyper Parameter Tuning in Machine Learning IIT Machine Learning Image Processing in Machine Learning Recall in Machine Learning Handwriting Recognition in Machine Learning High Variance in Machine Learning Inductive Learning in Machine Learning Instance Based Learning in Machine Learning International Journal of Machine Learning and Computing Iris Dataset Machine Learning Disadvantages of K-Means Clustering Machine Learning in Healthcare Machine Learning is Inspired by the Structure of the Brain Machine Learning with Python Machine Learning Workflow Semi-Supervised Machine Learning Stacking in Machine Learning Top 10 Machine Learning Projects For Beginners in 2023 Train and Test datasets in Machine Learning Unsupervised Machine Learning Algorithms VC Dimension in Machine Learning Accuracy Formula in Machine Learning Artificial Neural Networks Images Autoencoder in Machine Learning Bias Variance Tradeoff in Machine Learning Disadvantages of Machine Learning Haar Algorithm for Face Detection Haar Classifier in Machine Learning Introduction to Machine Learning using C++ How to Avoid Over Fitting in Machine Learning What is Haar Cascade Handling Imbalanced Data with Smote and Near Miss Algorithm in Python Optics Clustering Explanation Generate Test Datasets for Machine Learning

Difference between AI/ ML/ Deep Learning
2019-09-16 08:00:43

Difference between AI/ ML/ Deep Learning

Now a day’s people are very much confused with the terms called artificial intelligence, machine learning, and deep learning. For them, it seems to be that all these three concepts are exactly the same, but in reality, they are interrelated to each other but are not same. So, let’s see how they differ from each other;

Comparison between AIMLDeep Learning

Machine Learning

Before directly digging into the concept of machine learning, let’s first look at the term data mining. Basically, data mining is a practice that keeps on reviewing extensive data set and extracts some important information from that set only. So, it can be seen that machine learning works similarly as that of data mining or even we can say that it is one of kind of data mining.

“A subset of AI that contains some techniques permitting the computers to learn from past experiences without being programmed explicitly is what Machine Learning is.”

Machine learning is widely used by many big brands such as, online shopping apps like Amazon and Myntra etc in which they provide their customers with some suggestions based on their previous shopping or products reviewed, also Netflix gives recommendations to the users about the latest web series and shows that they would love to watch based on their previous watch and search history.

Deep Learning

Deep learning is a subpart of machine learning. It works in the same manner as that of machine learning does just the fact that it differs in terms of its ability.

In the case of Machine learning, the model becomes better while growing. If an error occurs, the programmers have to solve the issue by itself as the machine learning models require some supervision, but deep learning differs in this case as the model fixes itself. It did not require any help from the outside. A good example would be an automatic car driving system.

“Deep learning is a subset of machine learning used to decode complicated issues by learning from its own methods of computation.”

Artificial Intelligence

Machine learning and deep learning are further the subsets of artificial intelligence. AI is entirely different from ML and Deep learning. AI is hiking up so fast these days due to its concept that the machine has to imitate exactly like a human brain while solving the problems and learning. It has good potential to outperform for the company’s growth reinventing some new ideas by changing its way of work.

“An ability of a computer or machine to work the same as the human brain is called Artificial Intelligence.”

AI means to copy the human brain in such a way that it performs exactly how a human brain would in any particular situation by thinking and functioning just like a human. AI is still under growth but has achieved a lot by so far, and the best example to take into the account would be the Sophia an advancement of AI, Siri, etc. It does not need to be preprogrammed, and rather it uses algorithms which works for its intelligence. It incorporates Reinforcement learning, deep learning neural networks.