Machine Learning | LIVEWIRE

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Nowadays all are looking for a good profession. But don't know where to start and what to study. Have you people think about the upcoming technologies and future scopes. Machine Learning is one of the topmost technology that can change your life. Machine Learning (ML) prompts computers to run algorithms without being explicitly programmed. An interesting fact is that we people are using machine learning-powered devices many times in a day without even noticing it.  Machine learning algorithms are used in many applications, such as email filtering, and computer vision, where it is infeasible to develop an algorithm of specific instructions for performing the task.

 Mainly there are three types of Machine Learning Algorithms:

1. Supervised Learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks):
This algorithm consists of a target/outcome variable (or dependent variable) to be predicted from a specified set of predictors (autonomous variables). Using these variables, we generate a function that map inputs to desired outputs.

2. Unsupervised Learning (clustering, dimensionality reduction, recommender systems, deep learning):
We have no target or result variable that we can predict / estimate for this algorithm. It is used in various organizations to cluster population, which is widely used for segmenting customers in different groups for specific intervention.

3. Reinforcement Learning:
The machine is trained to create particular choices using this algorithm. It operates as follows: the machine is constantly subjected to a test and error setting. This machine draws on previous experience and attempts to gain the finest understanding possible to take correct business choices. Example of Reinforcement Learning: Markov Decision Process.

Commonly used Machine Learning algorithms are:

1. Decision Tree
2. Logistic Regression
3. Gradient Boosting algorithms
4. Random Forest
5. Naive Bayes
6. kNN
7. K-Means
8. SVM
9. Dimensionality Reduction Algorithms
10. Linear Regression

Examples of machine learning:

We all use Facebook in our daily lives. The interesting fact is that we are dealing with machine learning through facebook. Facebook's News Feed is personalizing News Feeds according to the user. This is done by using Machine Learning. If you daily scrolling to read or like a particular friend's posts, the News Feed will start to show more of that friend's activity earlier in the feed. So here the statistical analysis and predictive analytics techniques are used to identify the user's data to customize the News Feed.
Self-driving cars, Customer relationship management (CRM) systems, Human resource (HR) systems are some of the fields using ML.

Scopes:

Most of the companies need high skilled Machine Learning Engineers all over the world. The chances are increasing day by day. Livewire is a better option to learn Machine Learning with the help of highly skilled certified faculties. And also providing an Internationally recognized Certificate that results in getting a job in top class companies. Livewire is in association with 250+ corporates for ensuring a better placement. For the following experts we suggest this Machine Learning course in specific:

->Data Scientists
->Business Analytics
->Analytic Managers
->Analytic Professionals
->Information Architects
->All graduates who are interested in Machine Learning

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