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Deep Learning Calculus Data Science Machine Learning Ai




Machine Learning Certification Course


Freshers and Career Changers


Regular Offline and Online Live Training


Week Days and Week Ends

Duration :

2 Months

Machine Learning What will you learn?

•Learn to use tools in Machine Learning.See how to build a Machine Learning code.
•Learn to code with Machine Learning the easy way.
•Learn Machine Learning with Practical Hands-On Exercises for beginners
•From A-Z: The Complete Beginners-Advanced Masterclass – Learn Machine Learning
•Master the latest version of Machine Learning and create real projects
•Get straight to the point! Learn the basics of Machine Learning
•Learn Machine Learning from Scratch and Achieve Highest Knowledge with Practical Examples
•with this time saving course you will Learn Machine Learning and ready to use it

deep learning calculus data science machine learning ai Training Features

•24 × 7 = 365 days supportive faculty
•Course has been framed by Industry experts
•Highly competent and skilled IT instructors
•Personal attention and guidance for every student
•Assignments and test to ensure concept absorption.
•100% Guaranteed Placements Support in IT Companies with Big Salaries
•Our trainers have experience in training End Users & Students & Corporate employees.
•We do Schedule the sessions based upon your comfort by our Highly Qualified Trainers and Real time Experts

Who are eligible for Machine Learning

•Artificial Intelligence, Data Science, Block Chain, Iot, Cloud Computing, Ux Design, Mobile Application Development, Natural Language Processing, Business
•Front End, Javascript, Computer Graphics, Html, Css, Problem Solving, CSS, Web Technologies, Design, Software Development, Full Stack Developer
•JSF, hibernate, spring, Java SE 6 Developer, Sun Certified Developer for Java 2 Platform / Oracle Certified Master, html
•React.js, core, .net Core, React Native, Front End Developers, .Net Developers, .Net Tech Leads
•Software Engineer, Software Developer, Business Analyst, manager, Delivery Manager, Team Lead, .Net Framework, Java Framework, Mobile Application Development


Understanding the Function
•Calculus Basics
•Finding a Derivative
•Exercise 1 – Finding the Derivative
•Exercise 1 – Completion confirmation
•1 question
•Derivatives using Delta Method
•Exercise – 2
•Exercise – 2 – Completion confirmation
•Product Rule for Differentiation
•Exercise – 3
•Exercise – 3 – Completion confirmation
•Chain Rule
•Exercise – 4
•Exercise – 4 – Completion confirmation
•Applying all the basics
•End of Section 1
•Multi Variate Calculus
•Exercise – 5
•Exercise – 5 – Completion confirmation
•Differentiate With respect to anything
•Exercise – 6
•Exercise – 6 – Completion confirmation
•Exercise – 7
•Exercise – 7 – Completion confirmation
•Exercise – 8
•Exercise – 8 – Completion confirmation
•Chain Rule on Multi-Variate Functions
•Chain Rule on Multi Variate
•Chain Rule on Multi Variate – more functions
•Taylor Series of Approximations
•Taylor Series of Approximation
•Concept of Approximation
•Taylor Series – Intuition
•Taylor Series Detailed
•Taylor Series Derivation
•Taylor Series Derivation Part 2
•Taylor Series – More
•Neural Networks
•Neural Networks – Intro
•Bias in Neural Networks
•Neural Networks Part 2
•Calculus in Action – Neural Networks
•Intuition of Sigmoid Function
•Manual Fitting of Data
•Loss Function
•How to Update Parameters
•Compute Partial Derivative
•Exercise to compute Partial derivative of parameter – bias
•Program overview
•Program in Python
•Optimization Methods – Newton Raphson & Gradient Descent
•Newton Raphson Method
•Newton Raphson Method in Python
•Gradient Descent
•Linear Regression
•Linear Regression in Python
•Evaluation of Model – RMSE and R2 Score
•Implementation using Scikit Library
•Exercise 1 – Solution
•Exercise 2 – Solution
•Exercise 3 – Solution
•Exercise 4 – Solution
•Exercise 5 – Solution
•Exercise 6 – Solution
•Exercise 7 – Solution
•Exercise 8 – Solution
•Python for Data Science – Refresh the Basics
•Source code download
•Installing & Using Jupyter Notebook
•Google Colab
•Basic Data Types
•Python Basics – Containers in Python
•Control Statements Python if..else
•Control Statements While & For
•Functions & Classes in Python
•Python for Data Science
•Python Numpy Basics
•Python Numpy Basics Contd
•Python Numpy
•Pandas in Python – Pandas Series
•Pandas DataFrame
•Pandas – Dealing with Missing Values
•Matplotlib – Density and Contour Plot
•Bonus Videos
•Bonus Access
•Deep Learning Computer Vision
•Linear Algebra Course Trailer
•Deep Learning from Scratch using Tensorflow
•Follow on Youtube for free content