About
Machine Learning Certified Professional (MLCP)
Machine learning is a crucial part of the rapidly expanding discipline of data science. Algorithms are trained to generate classifications or predictions using statistical approaches, revealing crucial insights in data mining initiatives. Following that, these insights drive decision-making within applications and enterprises, with the goal of influencing important growth KPIs. As big data expands and grows, the demand for data scientists will rise, necessitating their assistance in identifying the most relevant business questions and, as a result, the data needed to answer them.
Objectives:
Machine learning's goal is to find patterns in your data and then generate predictions based on those patterns, which are typically complicated, in order to answer business questions, detect and analyse trends, and solve problems.
Prerequisites
You should be familiar with statistics, probability, linear algebra, and calculus, as well as programming languages and data modelling. Machine Learning is a lucrative professional path to pursue, but it takes some practice and experience.
What is
What is machine learning?
Machine learning is a branch of artificial intelligence (AI) that allows computers to learn and improve on their own without having to be explicitly programmed. Machine learning is concerned with the creation of computer programmes that can access data and learn on their own.
The learning process starts with observations or data, such as examples, direct experience, or instruction, so that we can seek for patterns in data and make better decisions in the future based on the examples we provide. The fundamental goal is for computers to learn on their own, without the need for human involvement, and to change their behavior accordingly.
However, text is treated as a series of keywords when using traditional machine learning algorithms; instead, a semantic analysis technique mimics the human ability to comprehend the meaning of a document.
Benefits
What are the benefits of machine learning?
Everything is becoming automated- Machine Learning is in charge of reducing workload and time. We let the algorithm perform the hard job for us by automating things. Automation is being practised in practically every industry. The reason for this is that it is quite dependable. It also aids our ability to think more imaginatively.
A diverse set of applications- There are numerous uses for machine learning. This means we can use machine learning in any of the key fields. ML is used in a variety of fields, including medicine, business, banking, research, and technology. This contributes to the creation of more opportunities. It has a significant impact on customer interactions.
Improvement Potential- Machine Learning is a technology that is always evolving. ML has a lot of potential to become the most important technology in the future. The reason for this is that it has a large number of research fields. This aids in the development of both hardware and software.
Data Handling in a Timely and Efficient Manner- Many factors contribute to the reliability of machine learning. Data management is one of them. When it comes to data, machine learning is currently playing the most important role. It is capable of handling any type of data.
Best for Online Shopping and Education- In the future, machine learning will be the most effective instrument for education. It teaches pupils how to study using very creative methods
Why should we study machine learning?
- Learning machine learning opens up new job possibilities.
- Machine Learning Engineers are well compensated.
- Job opportunities in machine learning are on the rise.
- CIOs Bemoan a Scarcity of Machine Learning Expertise.
- Data Science and Machine Learning are inextricably connected.
Team
Our Team
200+ years of industry experience bringing in core strengths and industry network
Rajesh Kumar
DevOps Princial Architect & Co-founder, Cotocus.
Capt. Augustine Joseph
CEO, Jetexe
Shubhanshu Srivastava
Co-Founder at GoScale Technologies
Sandeep Aggarwal
Co-Founder at GoScale TechnologiesF.A.Q
Frequently Asked Questions
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What are the learning outcomes?
- Develop an understanding of what's involved in Data-driven model learning
- Recognize a wide range of learning methods
- Understand how to analyze data-driven models.
- Apply the algorithms to a real-world situation, optimize the models you've learned, and report on the expected accuracy you'll get from using them.
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Is machine learning reliant on coding?
Yes, if you want to work in artificial intelligence or machine learning, you'll need to know how to code.
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In AI, what is machine learning?
Machine learning (ML) is a sort of artificial intelligence (AI) that allows software applications to improve their prediction accuracy without being expressly designed to do so. In order to forecast new output values, machine learning algorithms use historical data as input.
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What is the purpose of machine learning?
Machine learning is utilized in many apps on our phones, including search engines, spam filters, websites that generate personalized recommendations, banking software that detects suspicious transactions, and speech recognition.
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What is the current state of machine learning?
Machine learning is frequently used in recommendation engines. Fraud detection, spam filtering, malware threat detection, business process automation (BPA), and predictive maintenance are all common applications.
Kshitiij Gupta
Ceo & Founder
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Abhinav Gupta, Pune
Designer
The training was very useful and interactive. Rajesh helped develop the confidence of all.
Indrayani, India
Store Owner
Rajesh is very good trainer. Rajesh was able to resolve our queries and question effectively. We really liked the hands-on examples covered during this training program.
Ravi Daur , Noida
Freelancer
Good training session about basic Devops concepts. Working session were also good, howeverproper query resolution was sometimes missed, maybe due to time constraint.
Sumit Kulkarni
Software Engineer
Very well organized training, helped a lot to understand the DevOps concept and detailed related to various tools.Very helpful.
Vinaya
Software Engineer
Thanks Rajesh, Training was good, Appreciate the knowledge you poses and displayed in the training.
