Is Machine Learning Right for You?

The world today has been technologically changed by machine learning and big data analytics. Our challenges today, lie in understanding the large volumes of data we have created and using it intelligently. 

That is precisely what Machine Learning, Artificial Intelligence and machine learning courses in India have helped us with.Examples are everywhere and especially on your smartphone. ML has helped understand your shopping preferences and auto-suggests what you could be interested in. The same thing happens when you use your Facebook account which tags your friends and suggests videos that may interest you.

The Data Analyst and ML Engineer Roles
As a Data Analyst, your end goal is to use data to produce insights that are actionable by other humans. The ML Engineer does the same. However, its end goal is used by artificial intelligence systems to make the machines or systems behave in a particular way. This decision will impact the service or product and eventually the success of the enterprise.

Skills Required
ML requires a mix of skills to understand the complete environment, the how and the why of the issues you are designing and dealing with. Machine learning courses should ideally cover

Computer Science and Programming
Fundamentals including data structures, algorithms with their functioning, complex and complete solutions, approximation in algorithms, and system architecture. Hackathons, competitions in coding and plenty of practice are best at honing skills.

Statistics and Probability
The engine for ML runs on these and helps it in validating and building models from the provided algorithm which evolves from statistical models.

Evaluation and Data Modeling
These are important as ML build the model based on measures, weights, models, iterative algorithms and strategies it develops depending on its learning from the base algorithm.

Applying Libraries and ML Algorithms
Libraries and APIs like Theano, Scikit-learn, Tensor Flow etc., need a precise model and effective application for success.

Software Engineering and System Design
Output depends on the software and its design for applicability to provide robust, scalable and efficient solutions.

Job Roles with Demand
Data analysts, core ML engineers, applied ML engineers, and ML software engineers are jobs that will exponentially rise. Skills and Big data Hadoop training courses that help in applying ML algorithms and libraries will stand you in good stead. System design and software related jobs using ML, data modeling and evaluation, ML probability and statistics experts, and CS fundamentals and programming specialists jobs offer huge potential for professional development in the near future.

The Future of Machine Learning
Machine Learning, data analytics, AI and predictive analysis has no limits to its applicability and has already impacted every field like health, computers, life sciences, banking, education, insurance, finance, and literally every field you can think of.

Your weather forecasts, prices on stock exchanges, trends for the next decade, oil exploration, the MRI machines, predicting the subsequent breakdown, strategy building for marketing, automatic machine lines, and production are all today complex uses of techniques of using machine learning and AI for data analysis, analytics and predictive analysis. Will there be any field that is not impacted then by ML in the future?

If ML interests you then now is the time to update your knowledge and upgrade your skill-sets. There are courses and materials readily available. However, you will need a plan of action that you must adhere to. Good Luck!

Why Knowing Python Is Essential For AI And Machine Learning?

Getting started in a field like machine learning or artificial intelligence can be a challenge. Due to the numerous coding mechanism sand tools available to help you program your potential AI software, using an open-source tool like python is considered an essential skill. Python is one of the easiest coding languages around today and is also one of the most versatile and wide-spreading tools available.

To learn Machine Learning and AI you will need a specific language. There are several languages that one can learn including C++, Java, and R. However, most industry experts agree that Python is one of the best places to start. It has a well-stocked library and comes with an extensive and diverse toolkit.

Here is a closer look at how you can chart your learning of Python for Machine Learning and AI.

  1. Learn the Syntax

Python is all about the various syntax. The good news is that you do not have to learn all of it. However, there is no getting around learning the basic syntax of Python. With this step, it is recommended that you do not spend too much time on it. A few days, up to a week, is enough to learn the basic syntax of Python as you can always refer to it later.

There are many places on the web where you can familiarize yourself with artificial intelligence courses including on the main Python website.Other web pages include Imarticus Learning who teach Python with learning data science as the end game.