Machine Learning Data Science Deep Learning Neural Networks

Course details

Do you want to become a Data Scientist? Are you willing to learn Machine Learning? Well you're at the right place!!

The average salary for a Machine Learning Engineer is $138,920 per year in the United States by Indeed.

Machine learningis a field ofcomputer sciencethat uses statistical techniques to givecomputer systemsthe ability to "learn" (e.g., progressively improve performance on a specific task) withdata, without being explicitly programmed ~ by Wikipedia.

Machine learning can easily consume unlimited amounts of data with timely analysis and assessment.This method helps review and adjusts your message based on recent customer interactions and behaviors. Once a model is forged from multiple data sources, it has the ability to pinpoint relevant variables. This prevents complicated integrations, while focusing only on precise and concise data feeds.

Machine learning algorithms tend to operate at expedited levels.In fact, the speed at which machine learning consumes data allows it to tap into burgeoning trends and produce real-time data and predictions

1.Churnanalysis- it is imperative to detect which customers will soon abandon your brand or business. Not only should you know them in depth - but you must have the answers for questions like "Who are they? How do they behave? Why are They Leaving and What Can I do to keep them with us?"

2.Customerleads and conversion- you must understand the potential loss or gain of any and all customers. In fact, redirect your priorities and distribute business efforts and resources to prevent losses and refortify gains. A great way to do this is by reiterating the value of customers in direct correspondence or via web and mail-based campaigns.

3.Customerdefections- make sure to have personalized retention plans in place to reduce or avoid customer migration. This helps increase reaction times, along with anticipating any non-related defections or leaves.

Many hospitals use this data analysis technique to predict admissions rates.Physicians are also able to predict how long patients with fatal diseases can live.

Insurance agencies across the world are also able to do the following:

• Predict the types of insurance and coverage plans new customers will purchase.

• Predict existing policy updates, coverage changes and the forms of insurance (such as health, life, property, flooding) that will most likely be dominant.

• Predict fraudulent insurance claim volumes while establishing new solutions based on actual and artificial intelligence.

Machine learning is proactive and specifically designed for "action and reaction" industries.In fact, systems are able to quickly act upon the outputs of machine learning - making your marketing message more effective across the board.

So in this course Machine Learning, Data Science and Neural Networks + AI we will discover topics:

• Introduction

• Supervised Learning

• Bayesian Decision Theory

• Parametric Methods

• Multivariate Methods

• Dimensionality Reduction

• Clustering

• Nonparametric Methods

• Decision Trees

• McNemars Test

• Hypothesis Testing

• Bootstrapping

• Temporal Difference Learning

• Reinforcement Learning

• Stacked Generalization

• Combining Multiple Learners

• d-Separation

• Undirected Graphs: Markov Random Fields

• Hidden Markov Models

• Regression

• Kernel Machines

• Multiple Kernel Learning

• Normalized Basis Functions

• The Perceptron

• and much more!!