Kennith  Kuhic

Kennith Kuhic

1621353060

Machine Learning vs Data Analytics: Difference Between Machine Learning and Data Analytics

Machine learning vs data analytics is one of the most talked-about topics among data science aspirants. Both of these fields focus on data and are among the most in-demand sectors. Thus, while choosing a data science career, it is quite natural to feel confused about these two trending domains.

But worry not, for we’ve created the perfect guide to help you understand the difference between machine learning and data analytics.

Now, let’s get straight to the topic at hand – machine learning vs data analytics.

Machine Learning vs Data Analytics: Definition

To understand the difference between machine learning and data analytics, we must first look at their definitions. They will help you understand what makes these fields unique and different from each other.

What is Machine Learning?

Machine learning refers to the study of algorithms that improve through experience. It is related to artificial intelligence. A machine learning algorithm learns from data automatically and applies the learning without requiring human intervention.

Machine learning has multiple branches and there are various methods to use them. Conventional machine learning solutions use predictive analysis and statistical analysis for finding patterns and catching hidden insights into the available data.

One of the best examples of machine learning at work is Netflix’s recommender system, which suggests movies and shows automatically based on collaborative and content-based filtering.

What is Data Analytics?

Data analytics, also known as data analysis, is the process of cleaning, inspecting, modelling, and transforming data for finding valuable information, informing conclusions and enhancing the decision-making process.

Data analytics focuses on generating valuable insights from the available data. Companies use data analytics to make better-informed decisions regarding various matters including marketing, production, etc. Data analytics helps you take raw data and extract helpful information from the same.

As you can see, a key difference between machine learning and data analytics is in how they use data. Data analytics focuses on using data to generate insights while machine learning focuses on creating and training algorithms through data so they can function independently.

Machine Learning vs Data Analytics: Salary

In terms of pay, there’s a notable difference between machine learning and data analytics.

Machine Learning Salary in India

The average pay for a machine learning professional in India is INR 6.86 lakh per annum including shared profits and bonuses. Freshers in this field make around INR 3 lakh per annum on average. However, an experienced machine learning professional can get up to INR 20 lakh per year on average. It’s certainly one of the most lucrative sectors out there.

Machine learning professionals in Bangalore and Chennai earn considerably more than the national average while the machine learning professional in Delhi and Pune earn 25% and 10% less than the average.

#data analytics #machine learning #machine learning #data analytics

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Buddha Community

Machine Learning vs Data Analytics: Difference Between Machine Learning and Data Analytics
Kennith  Kuhic

Kennith Kuhic

1621353060

Machine Learning vs Data Analytics: Difference Between Machine Learning and Data Analytics

Machine learning vs data analytics is one of the most talked-about topics among data science aspirants. Both of these fields focus on data and are among the most in-demand sectors. Thus, while choosing a data science career, it is quite natural to feel confused about these two trending domains.

But worry not, for we’ve created the perfect guide to help you understand the difference between machine learning and data analytics.

Now, let’s get straight to the topic at hand – machine learning vs data analytics.

Machine Learning vs Data Analytics: Definition

To understand the difference between machine learning and data analytics, we must first look at their definitions. They will help you understand what makes these fields unique and different from each other.

What is Machine Learning?

Machine learning refers to the study of algorithms that improve through experience. It is related to artificial intelligence. A machine learning algorithm learns from data automatically and applies the learning without requiring human intervention.

Machine learning has multiple branches and there are various methods to use them. Conventional machine learning solutions use predictive analysis and statistical analysis for finding patterns and catching hidden insights into the available data.

One of the best examples of machine learning at work is Netflix’s recommender system, which suggests movies and shows automatically based on collaborative and content-based filtering.

What is Data Analytics?

Data analytics, also known as data analysis, is the process of cleaning, inspecting, modelling, and transforming data for finding valuable information, informing conclusions and enhancing the decision-making process.

Data analytics focuses on generating valuable insights from the available data. Companies use data analytics to make better-informed decisions regarding various matters including marketing, production, etc. Data analytics helps you take raw data and extract helpful information from the same.

As you can see, a key difference between machine learning and data analytics is in how they use data. Data analytics focuses on using data to generate insights while machine learning focuses on creating and training algorithms through data so they can function independently.

Machine Learning vs Data Analytics: Salary

In terms of pay, there’s a notable difference between machine learning and data analytics.

Machine Learning Salary in India

The average pay for a machine learning professional in India is INR 6.86 lakh per annum including shared profits and bonuses. Freshers in this field make around INR 3 lakh per annum on average. However, an experienced machine learning professional can get up to INR 20 lakh per year on average. It’s certainly one of the most lucrative sectors out there.

Machine learning professionals in Bangalore and Chennai earn considerably more than the national average while the machine learning professional in Delhi and Pune earn 25% and 10% less than the average.

#data analytics #machine learning #machine learning #data analytics

Nora Joy

1607006620

Applications of machine learning in different industry domains

Machine learning applications are a staple of modern business in this digital age as they allow them to perform tasks on a scale and scope previously impossible to accomplish.Businesses from different domains realize the importance of incorporating machine learning in business processes.Today this trending technology transforming almost every single industry ,business from different industry domains hire dedicated machine learning developers for skyrocket the business growth.Following are the applications of machine learning in different industry domains.

Transportation industry

Machine learning is one of the technologies that have already begun their promising marks in the transportation industry.Autonomous Vehicles,Smartphone Apps,Traffic Management Solutions,Law Enforcement,Passenger Transportation etc are the applications of AI and ML in the transportation industry.Following challenges in the transportation industry can be solved by machine learning and Artificial Intelligence.

  • ML and AI can offer high security in the transportation industry.
  • It offers high reliability of their services or vehicles.
  • The adoption of this technology in the transportation industry can increase the efficiency of the service.
  • In the transportation industry ML helps scientists and engineers come up with far more environmentally sustainable methods for powering and operating vehicles and machinery for travel and transport.

Healthcare industry

Technology-enabled smart healthcare is the latest trend in the healthcare industry. Different areas of healthcare, such as patient care, medical records, billing, alternative models of staffing, IP capitalization, smart healthcare, and administrative and supply cost reduction. Hire dedicated machine learning developers for any of the following applications.

  • Identifying Diseases and Diagnosis
  • Drug Discovery and Manufacturing
  • Medical Imaging Diagnosis
  • Personalized Medicine
  • Machine Learning-based Behavioral Modification
  • Smart Health Records
  • Clinical Trial and Research
  • Better Radiotherapy
  • Crowdsourced Data Collection
  • Outbreak Prediction

**
Finance industry**

In financial industries organizations like banks, fintech, regulators and insurance are Adopting machine learning to improve their facilities.Following are the use cases of machine learning in finance.

  • Fraud prevention
  • Risk management
  • Investment predictions
  • Customer service
  • Digital assistants
  • Marketing
  • Network security
  • Loan underwriting
  • Algorithmic trading
  • Process automation
  • Document interpretation
  • Content creation
  • Trade settlements
  • Money-laundering prevention
  • Custom machine learning solutions

Education industry

Education industry is one of the industries which is investing in machine learning as it offers more efficient and easierlearning.AdaptiveLearning,IncreasingEfficiency,Learning Analytics,Predictive Analytics,Personalized Learning,Evaluating Assessments etc are the applications of machine learning in the education industry.

Outsource your machine learning solution to India,India is the best outsourcing destination offering best in class high performing tasks at an affordable price.Business** hire dedicated machine learning developers in India for making your machine learning app idea into reality.
**
Future of machine learning

Continuous technological advances are bound to hit the field of machine learning, which will shape the future of machine learning as an intensively evolving language.

  • Improved Unsupervised Algorithms
  • Increased Adoption of Quantum Computing
  • Enhanced Personalization
  • Improved Cognitive Services
  • Rise of Robots

**Conclusion
**
Today most of the business from different industries are hire machine learning developers in India and achieve their business goals. This technology may have multiple applications, and, interestingly, it hasn’t even started yet but having taken such a massive leap, it also opens up so many possibilities in the existing business models in such a short period of time. There is no question that the increase of machine learning also brings the demand for mobile apps, so most companies and agencies employ Android developers and hire iOS developers to incorporate machine learning features into them.

#hire machine learning developers in india #hire dedicated machine learning developers in india #hire machine learning programmers in india #hire machine learning programmers #hire dedicated machine learning developers #hire machine learning developers

 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

sophia tondon

sophia tondon

1620898103

5 Latest Technology Trends of Machine Learning for 2021

Check out the 5 latest technologies of machine learning trends to boost business growth in 2021 by considering the best version of digital development tools. It is the right time to accelerate user experience by bringing advancement in their lifestyle.

#machinelearningapps #machinelearningdevelopers #machinelearningexpert #machinelearningexperts #expertmachinelearningservices #topmachinelearningcompanies #machinelearningdevelopmentcompany

Visit Blog- https://www.xplace.com/article/8743

#machine learning companies #top machine learning companies #machine learning development company #expert machine learning services #machine learning experts #machine learning expert

Get Started With Big Data Analytics For Your Business

We live in a world where billions of data points are generated every single day from different sources, such as banks, telecommunication companies, industries, tourism, the agriculture sector, educational institutions (primary, secondary, colleges, and universities), and mobile devices. Any organization can start using their data to make data-driven decision-making that is effective and supportive of their mission and vision.

Regardless of the size of the business you’re running, you need valuable data to provide you with business insights. The insights help you to know your target audience and their preferences, and as a result, your business will be able to anticipate their needs. You can use insights from big data to outperform your competition by capturing and innovating through big data.

Companies like Google and Alibaba are using it to discover flaws in their services and products, suppliers and buyers, and consumer intent and preferences so they can create newer, better ones.

#data #data-science #big-data #big-data-analytics #analyzing-big-data #artificial-intelligence #machine-learning #data-analytics