Learn practical machine learning from NetTech India & get certification with placement Assistance at affordable fees in Andheri, Thane. NetTech Machine learning training will make you master in the field of machine learning, a kind of artificial intelligence that enables the computer to learn to do specific tasks through the instructions and explicit programming. NetTech India offers best machine learning courses in Mumbai and Thane. Through this Machine learning certification course in navi mumbai, the candidate will be able to learn the different techniques and concepts, including mathematical and heuristic aspects, hands-on modeling to develop the algorithm and to ultimately prepare you for the job of machine learning engineer.

What is a Machine Learning Language course?

The language is taking the world by strides- and with that, there is a growing demand of companies who need professionals who know the ins and outs of machine learning language. The machine learning language market size is expected to grow at the multifold rate from USD 1.03 billion to USD 8.82 billion by 2022, at a CAGR of 44.1%.

What are the Machine learning courses in mumbai objectives?

Machine learning is revolutionizing the world of computing by making the process of computing easy. It is a quick and easy way to analyze a vast amount of complex data. Machine learning seems to be the future of learning. The automated technologies like facial recognition not only help fraud prevention but also help in improved productivity. NetTech Machine learning course in Mumbai is best for engineers, data scientists and professionals who want to gain competency in the field of machine learning. The demand for machine learning skills is growing by leaps and bounds. The median salary of a machine learning professional is $134,293 as per the Payscale.

What skills will you accomplish?
  • After the completion of machine learning training programme, you will be able to
  • Master the concepts of reinforcement, supervised and unsupervised learning concepts and modeling
  • Gain practical experience on principles, algorithm and application related to machine learning language through hands-on projects
  • Will help you to acquire knowledge about mathematical and heuristic concepts related to machine learning
  • Understand the different concepts related to kernel SVM, random forest, K nearest, clustering, and much more.
  • Learn theoretical concepts related to machine learning and apply it in a practical way.
  • Learn robust machine learning algorithm including clustering, deep learning and recommendation

To whom this machine learning course is suitable for?

The demand for machine engineers is on the rise across different industries making this course suited for the professionals with intermediate experience. This course is suitable for the professionals.

  • For the aspiring data scientist or machine engineer
  • Data analytics who is keen to learn data science techniques
  • Information architects who want to learn about machine learning algorithm
  • Analytics professionals who want to learn machine learning or artificial intelligence
  • Graduates who want to build their career in the field of data science and machine learning
  • Experienced professionals who want to harness machine learning language in the field to its advantage.

  • Introduction to Machine Learning
  • Types of Machine learning
  • Data understanding: real-life example
  • Application of Machine Learning
  • Discussion on different packages used for ML
  • Related concepts: Splitting the dataset into train set and test set
  • Practical knowledge of the algorithm on Python

  • Descriptive statistics: Measure of Central Tendency, Measure of Dispersion, Measure of Shape
  • Probability and sampling: Conditional probability, Bayes theorem
  • Probability Distribution
  • Use Column Heading Defaults
  • Hypothesis Test

  • Numpy
  • Pandas
  • Matplotlib
  • Seaborn

  • Introduction to Graphs
  • Description about data
  • Visualisation
  • Data cleaning

  • Scaling
  • Normaliztion
  • Standardization

  • Linear Regression Technique
  • Dataset with problem description
  • Non- Linear Regression Techniques
  • Logistic Regression Technique

  • K-Nearest Neighbors
  • Concept and theory
  • Distance functions: Euclidean, Minkowski
  • Why should we use KNN?
  • Mathematical approach
  • Dataset with problem description
  • Practical application on Python

  • Support Vector machine
  • Introduction to Support Vector Machine
  • Mathematical Approach
  • Theory on hyperplane
  • Dataset with problem description
  • Practical application on Python

  • Introduction to Decision Tree
  • Significance of using Decision Tree
  • Different kinds of Decision Tree
  • Procedure and technique of Decision Tree
  • Practical application of Decision Tree on Python

  • Random Forest
  • Theory and mathematical concepts
  • Entropy and Decision Tree
  • Dataset with problem description
  • Classification using random forest on Python

  • Introduction of Naïve Bayes
  • Theory of classification
  • Concept of probability: prior and posterior
  • Bayes Theorem
  • Mathematical concepts
  • Limitation of Naïve Bayes
  • Dataset with problem description
  • Practical application on Python

  • Introduction of clustering
  • K-mean clustering
  • Hierarchical Clustering
  • Dataset with problem description
  • Practical application on Python

  • Gradient descent
  • Stochastic GradientDescent
  • Gradient boosting
  • Types of boosting
  • Bootstrapping
  • Practical application on Python

  • Linear Discriminant Analysis (LDA)
  • Principal component Analysis (PCA)
  • Business case study

  • Introduction to time series
  • Components of Time Series: Trend, Seasonal, Cyclical
  • Types of Forecasting methods: Autoregressive Model, Moving Average Model, Autoregressive Integrated Moving Average Model, Seasonal Autoregressive Integrated Moving Average Model
  • Practical application on Python
Our Certification
  • NetTech India
**@Extra Cost Certification Options Available
  • IBM
Career Opportunity After Completing Machine Learning Course in Mumbai:
  • Software Engineer
  • Python Developer
  • Research Analyst
  • Data Analyst
  • Data Scientist
  • Software Developer
  • Data analytics
  • Cell and UI development
  • BigData Analyst
  • Business Analyst
  • Data Research Analyst
  • IT Consultant Desktop Application Developer
  • 6000+ Sq.Ft of Area
  • Practical Training on Live Projects
  • Placement Training
  • Complete Placement Assistance
  • Mock Interviews
  • Assignment
  • Global Certification
  • Free Demo Lecture
  • Study Materials
  • Training from Industry Expert


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