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Rock Machine Learning with Python - Multiple LIVE Coding

Learn Machine Learning with 30+ LIVE Coding ?‍♂️ Statistics, Data Analysis, Linear,Logistic Regression,KNN, SVM
Course from Udemy
 874 students enrolled
 en
Machine Learning, Deep Learning, AI and Data Science Basic Concepts
Applications of ML/AI/DS and Job prospects
Supervised, Un-supervised Learning
Environment Setup : Anaconda and Jupyter Notebook
Python package “Numpy” for numerical computation, Python package “Matplotlib” for visualization and plotting, Python package “pandas” for data analysis
Basics of Probability Theory
Understanding different types of data
Examining distribution of the variables
Examining relationship among variables
Exploratory data analysis using Python
Linear regression model / hypothesis
Linear regression on bi-variate data
Multivariate Regression
Polynomial regression
Python implementation of Gradient descent algorithm for regression.
Using in-built Python libraries for solving linear regression problem.
Logistic regression for binary classification problem.
Logistic regression for multiclass classification problem.
Python implementation of Gradient Descent update rule for logistic regression.
Using Python built in library for logistic regression problem.
K-Nearest Neighbour Classifier, Naïve Bayes Classifier, Decision Tree Classifier, Support Vector Machine Classifier, Random Forest Classifier (We shall use Python built-in libraries to solve classification problems using above mentioned classification algorithms)
High dimensionality in data set and its problems.
Linear Algebra Review: Eigen value decomposition.
Feature Selection and Feature Extraction techniques
Principal Component Analysis (PCA)
Implementation of PCA in python.
k-Means clustering algorithm and its limitation
Implementation of k-Means clustering algorithm in python
Hierarchical Clustering.
Implementation of Hierarchical clustering in Python.
Perceptron and its learning rule and its limitations.
Multi-layered Perceptron (MLP) and its architecture.
Learning Rule : Back-Propagation
Building an MLP in Python.

Machine Learning is everywhere from Tiktok video suggestion, Facebook friend suggestion, self-driving car to analyzing website data to get more profit ML is used everywhere you nowadays!


Do you want to ROCK the Machine Learning to get Boost in Your CV or to get a New Job?

Than is hands On Course is Just for You!


This course is designed for beginner level students who want to move into the amazing field of Machine Learning and want to Rock their Career!


In this beginner-friendly course you are going to Learn:


  • Environment Setup

  • Statistics and Exploratory Data Analysis

  • Simple Linear Regression

  • Multiple Linear Regression

  • Advanced Regression

  • Logistic Regression

  • K-Nearest Neighbour Classifier (KNN)

  • Support Vector Machine Classifier (SVM)

  • Naive Bayes Classifier

  • Decision Tree

  • Dimensionality Reduction

  • Unsupervised Learning

  • Artificial Neural Network


Why Choose the Course?


  • Hands On Coding on Each Topic

  • Study Note for Each Lecture

  • Quizzes

  • 24x7 Support

  • Top-Notch Instructor


Meet Your Instructor:


This Course is taught by Mr. Sourav who has 4 Years Of Experience in AI and ML and worked in different companies.

He has real-life Industry Experience in AI and ML.


This Course Comes with 30 Days Money Back Guarantee. If you are NOT satisfied anyhow you will get your FULL Money Back. No Question Asked.


Rock Machine Learning with Python - Multiple LIVE Coding
$ 94.99
per course
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