• Live sessions
  • Practice-based learning
  • 100% job assistance

Highlights of Our Course

The highlights of our Machine Learning course are listed here.

  • Learning at your speed
  • Case Studies & Industry Projects
  • Sessions in Real-Time
  • Training with an instructor
  • Mentoring Sessions One-on-One
  • Assistance with a Job

What will you learn in the Machine Learning Course?

In this certification program, you'll learn the fundamentals of Machine Learning. You'll be given step-by-step lessons on how to master machine learning. This is the best machine learning course, and it will teach you everything you need to know about the subject.

  • Learn advanced data analysis techniques
  • Make Machine Learning solutions for a variety of business issues.
  • Create and deploy Machine Learning applications that are fit for production
  • Immediately implement Machine Learning approaches, techniques, and technologies

Framework of Our Certification Program

Choose a specialty area

My Learning Course offers a variety of specialization courses from which you may pick whichever one you need to learn. Consider enrolling in our Machine Learning expert course, which will assist you in breaking into this exciting field.

Participate in live sessions

You will be allowed to attend the lectures once you have finished your online registration for the machine learning course. Master Machine Learning principles, methods, and approaches by attending live sessions led by industry professionals.

Get a recognized certification

You will acquire a certification after completing your Machine Learning full course. After gaining your certification, you'll be able to apply for a variety of machine learning positions all across the world.

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An Introduction to Machine Learning Courses 

There are several Machine Learning Courses for beginners and intermediate and advanced levels available on the market. A professional course covers machine learning, data mining, and statistical pattern identification in depth. Machine Learning is proven to be among the major game-changing technology breakthroughs in the last decade. In today's increasingly competitive business world, machine learning is allowing businesses to accelerate their digital transformation and move into the age of automation.

Some would even claim that Machine Learning is necessary to be relevant in certain industries, such as digital payments, banking fraud detection, and product suggestions. Anyone working in the computer sector nowadays should have a basic understanding of artificial intelligence and machine learning. An individual might participate in the best machine learning course online to get practical knowledge of the technology and boost their career.

What does the term "machine learning" mean?

Machine learning is a sort of AI that enables systems to learn and develop simultaneously without having to be explicitly designed. It is a method of noticing data patterns, gathering pertinent data, and making informed decisions for the betterment of any organization's future. Machine learning makes it easier to analyze large amounts of data, usually resulting in faster and more accurate results that can be used to extract financial benefits and possibilities.

Machine learning is currently employed in practically every other application and program on the Internet in some form or another. Machine Learning has grown in popularity to the point where it is now the go-to tool for businesses to solve a variety of problems. Several recognized institutions now offer machine learning courses in India that can help a person advance professionally in the field.

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Our Machine Learning Course Syllabus

My Learning Course

Qualified academic and industry specialists crafted our machine learning certification course. This online training plan covers the following topics.

  • What is Machine Learning?
  • Supervised Learning
  • Unsupervised Learning
  • Machine Learning Honor Code
  • How to Use Discussion Forums
  • Linear Regression with One Variable
  • Linear Algebra Review
  • Multiple Features
  • Gradient Descent for Multiple Variables
  • Features and Polynomial Regression
  • Normal Equation
  • Non Invertibility
  • Basic Operations
  • Moving Data Around
  • Computing Data
  • Plotting Data
  • Control Statements
  • Classification
  • Hypothesis Representation
  • Decision Boundary
  • Cost Function
  • Simplified Cost Function and Gradient Descent
  • Advanced Optimization
  • Multiclass Classification: One-vs-all
  • The Problem of Overfitting
  • Cost Function
  • Regularized Linear Regression
  • Regularized Logistic Regression
  • Non-linear Hypotheses
  • Neurons and the Brain
  • Model Representation
  • Examples and Intuitions I
  • Multiclass Classification
  • Cost Function
  • Backpropagation Algorithm
  • Backpropagation Intuition
  • Implementation Note: Unrolling Parameters
  • Gradient Checking
  • Random Initialization
  • Putting It Together
  • Autonomous Driving
  • Evaluating a Hypothesis
  • Model Selection and Train/Validation/Test Sets
  • Diagnosing Bias vs. Variance
  • Regularization and Bias/Variance
  • Learning Curves
  • Prioritizing What to Work On
  • Error Analysis
  • Error Metrics for Skewed Classes
  • Trading Off Precision and Recall
  • Data For Machine Learning
  • Error Analysis
  • Optimization Objective
  • Large Margin Intuition
  • Mathematics Behind Large Margin Classification
  • Kernels I, Kernels II
  • Using an Support Vector Machine
  • Introduction to Unsupervised Learning
  • K-Means Algorithm
  • Optimization Objective
  • Random Initialization
  • Choosing the Number of Clusters
  • Data Compression
  • Data Visualization
  • Principal Component Analysis Problem Formulation
  • Principal Component Analysis Algorithm
  • Reconstruction from Compressed Representation
  • Choosing the Number of Principal Components
  • Advice for Applying PCA
  • Problem Motivation
  • Developing and Evaluating an Anomaly Detection System
  • Gaussian Distribution
  • Multivariate Gaussian Distribution
  • Anomaly Detection vs. Supervised Learning
  • Anomaly Detection using the Multivariate Gaussian Distribution
  • Introduction to Recommendation
  • Problem Formulation
  • Content Based Recommendations
  • Collaborative Filtering
  • Collaborative Filtering Algorithm
  • Vectorization: Low Rank Matrix Factorization
  • Implementational Detail: Mean Normalization
  • Learning With Large Datasets
  • Stochastic Gradient Descent
  • Mini-Batch Gradient Descent
  • Stochastic Gradient Descent Convergence
  • Online Learning
  • Map Reduce and Data Parallelism
  • Problem Description and Pipeline
  • Sliding Windows
  • Getting Lots of Data and Artificial Data
  • Ceiling Analysis

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What are the various types of Machine Learning?

Machine learning is the study of a computer program, or algorithm and how to improve over time on a given task. Machine learning can be regarded through the lens of theoretical and mathematical modeling when it comes to research. However, the study of how to design applications that demonstrate this iterative progress is more practical. Supervised Learning, Unsupervised Learning, and Reinforcement Learning are the three types of machine learning. 

Supervised Learning

The most widely used machine learning technique is supervised learning. It is the easiest to comprehend and put into practice. Supervised learning is frequently defined as task-oriented. It is laser-focused on a specific goal, supplying the algorithm with more and more instances until it is able to perform the task correctly.

Unsupervised Learning

The polar opposite of supervised learning is unsupervised learning. There are no labels on it. Instead, we would feed our algorithm a large amount of data and provide it with the tools it needs to comprehend the data's features. It can learn to categorize data and then organize data in a way that a human or other intelligent program can understand.

Reinforcement Learning

Reinforcement learning is quite different if you compare it to supervised and unsupervised learning. The relationship between reinforcement learning and the presence or absence of labels is a little hazier. Whereas the association between supervised and unsupervised learning and the presence or lack of labels is clear. Some people try to link the two by categorizing reinforcement learning as a sort of learning that relies on a time-dependent sequence of labels.

What are machine learning's business applications?

Machine learning has progressed from the realm of science fiction to a critical component of today's industries, with companies in practically every industry employing various machine learning technologies. It is most typically utilized to solve data-intensive business problems. With each iteration, corporate machine learning apps employ the algorithms to learn from the data, whenever new data is entered, the system compares it to earlier entries automatically. 

Machine learning is used in businesses to improve scalability and create operations for them. The business analytics community has embraced artificial intelligence tools and numerous machine learning techniques. Individuals who want to become professionals can enroll in the best machine learning online course and apply the skills in real-world tasks. Machine learning has a wide range of applications in business, including the following.

Assistance in making decisions

Another area where machine learning systems may assist businesses is in transforming massive amounts of data into useful and actionable insights. Healthcare, agriculture, and business are just a few of the industries that use decision support systems..

Chatbots that operate in real-time

Chatbots, which have overcome the communication gap between people and technology, are among the earliest kinds of automation. It enables individuals to talk with machines, which can subsequently take action in response to the demands or requirements expressed by humans.

Modeling customer churn

Businesses also use machine learning to detect when customers' loyalty is diminishing, so they devise methods to fix the situation. The upgraded machine learning applications are used in this case to help businesses deal with one of the oldest, and most common problems, customer turnover.

Dynamic pricing strategies

Companies can use historical price data and data sets on a variety of other variables to better understand how different dynamics, such as time of day, weather, and seasons, affect demand for goods and services. Machine learning algorithms may learn from such data and integrate it with additional markets. 

Medical Prognosis

Due to the objectivity of data analysis, machine learning in healthcare can provide nearly perfect diagnoses. The computers can also help forecast readmissions, suggest the appropriate treatments, and identify high-risk patients, all based on patient data.

Recognize and classify images

Machine learning, deep learning, and neural networks are three sets of algorithms meant to discover patterns businesses use to help them understand images. Machine learning has a wide range of applications, ranging from Facebook's want to tag photographs shared on the site, to security teams' desire to detect illegal conduct in real-time.

Why should you learn Machine Learning with us?

We provide fantastic training for students who want to learn about a few key areas of machine learning, such as linear algebra and how algorithms work. This online Machine Learning course will teach you the skills you need to succeed as a Machine Learning Engineer. You will be able to apply all you have learned in your work, after enrolling in the best machine learning course in India with us.

My Learning Course

Who is eligible to participate in Machine Learning online courses?

  • 1

    Individuals having a bachelor's degree and a strong desire to learn more about Machine Learning.

  • 2

    IT professionals interested in a career change as Data Scientists or Artificial Intelligence Engineers.

  • 3

    Freshmen are interested in pursuing a career in Machine Learning and Data Science.

Machine Learning Engineering Course Job Opportunities

Machine learning is gaining traction around the world, and many people want to pursue a career in it. The number of jobs in machine learning has increased by over 75% over the last five years. Machine learning is one of the most in-demand professions right now. Voice assistants, facial recognition, self-driving cars, and e-commerce recommendation engines are all examples of modern applications that use machine learning. Data Scientist, Computer Vision Engineer, Data Architect, and Machine Learning Engineer are just a few of the key roles in the machine learning field. This field will remain important in the future, and experts who work in it can expect to make a solid career. As a first step, enroll in the best online courses for machine learning and study everything from the ground up.

Frequently Asked Questions (FAQs)

Our Machine Learning course syllabus is created by subject matter specialists who understand the abilities that businesses look for. Topics such as machine learning types, regression, time series modeling, clustering, classification, and deep learning principles are addressed in detail, allowing you to establish a career in this industry.

Machine learning is a hot topic right now. However, before diving into certificate programs, newbies should acquaint themselves with the fundamentals of machine learning. Principles and techniques can be learned through a Machine learning crash course, tutorials, and watching videos online.

Machine learning is a branch of artificial intelligence 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 programs that can access data and learn on their own.

Basic programming, statistics data modeling, Core arithmetic, natural language processing, neural networks, ML tools and libraries, and more are all expected of a Machine Learning Engineer. Every one of these skills will be imparted during our machine learning courses online, and you will be job-ready.

Our machine learning course will help you learn all of the fundamentals of machine learning methodically. The course is simple to follow and allows you to combine academic and practical knowledge of machine learning. This is the best machine learning course in Delhi, Noida, and is ideal for those with a prior understanding of statistics, mathematics, and Python programming.

All course materials, such as graded assignments, are included when you participate in our learning program. Your electronic Certification will be uploaded to your accomplishments section once you've finished the training, so you can add that to your LinkedIn profile from there. You can review the course for free if all you want to do is read and watch the material.