Python For Machine Learning With Solved Projects By Spotle

What you'll learn
Python fundamentals
Handling numbers in Python
Handling strings in Python
Control flow in Python
File handling in Python
Modules and packages in Python
Python libraries - numpy, pandas, matplotlib, scikit-learn etc
Basic statistics and data visualization with Python
Overview of machine learning
Supervised machine learning
Unsupervised machine learning
Linear regression with Python
Logistic regression with Python
Decision tree with Python
Regression tree with Python
Random forest with Python
Support Vector Machines with Python
K-means clustering with Python
Do It Yourself - hierarchical clustering
K-Nearest Neighbor
Naïve Bayes Classifier with Python
Do It Yourself - Build Your Own Credit Risk Analyzer
Requirements
You will need to have a computer or a mobile handset with an internet connection
Description
Machine learning and Python have become key industry drivers in the global job and opportunity market. This course with lectures from industry experts and Ivy League academics will help learners learn a wide range of machine learning techniques. Get ready for the experiential learning. All the topics have been explained with worked-out real projects with real data. The learners will get the chance to apply their learning in Do It Yourself projects. In this course you will learn:Python fundamentalsHandling numbers in PythonHandling strings in PythonControl flow in PythonFile handling in PythonModules and packages in PythonPython libraries - numpy, pandas, matplotlib, scikit-learn etcBasic statistics and data visualization with PythonOverview of machine learningSupervised machine learningUnsupervised machine learningLinear regression with PythonLogistic regression with PythonDecision tree with PythonRegression tree with PythonRandom forest with PythonSupport Vector Machines with PythonK-means clustering with PythonDo It Yourself - hierarchical clusteringK-Nearest NeighborNaïve Bayes Classifier with PythonDo It Yourself - Build Your Own Credit Risk AnalyzerSpotleSpotle is an AI-powered career platform matching you to the relevant career path in real-time. Spotle provides a dynamic and agile platform to discover career choices matched to your life goals.The AI based platform understands your aspiration and potential, analyses your career goals and automatically finds the right networks, career paths and opportunities for you. Think of it as your AI-enabled assistant working 24/7 to help your career grow. Powered by a mix of NLP, predictive modelling and machine learning, Spotle works in the background and automatically discovers for you the right opportunities, networks and career resources. The Spotle Learn platform develops and aggregates learnings and content from top academics and industry practitioners and helps you build your skill through an adaptive learning path.For companies or employers, Spotle uses deep matching to instantly surface the right talents you will want to hire. It simplifies the entire hiring process through AI-powered candidate matching. Your talent pipelining becomes easy as Spotle recommends potential hires based on your hiring goals and lets you engage with passive candidates who are not actively applying to jobs right now. It gives you a periscopic view into campus talents through leaderboards and innovative skill points.Spotle reaches over 20,000 Recruiters and a million plus students and young professionals. The company works with leading campuses and companies to craft the right career matches.
Overview
Section 1: Recap Python
Lecture 1 Setup Your Python Environment And Write Your First Program
Lecture 2 Introduction To Python
Lecture 3 Python Basics
Lecture 4 How Python Programs Can Be Run In Many Ways
Section 2: Numbers
Lecture 5 Numerical Operations With Python
Section 3: Strings
Lecture 6 String In Python
Lecture 7 String In Python - Codes
Section 4: Loops And Conditional Flow
Lecture 8 Python Control Flow - Part 1
Lecture 9 Python Control Flow - Part 2
Lecture 10 Python Control Flow - Part 3
Lecture 11 Python Control Flow - Codes
Section 5: File Operations
Lecture 12 File Handling In Python Part - 1
Lecture 13 File Handling In Python Part - 2
Lecture 14 File Handling In Python Part - 3
Lecture 15 File Handling In Python - Codes
Section 6: Modules And Packages
Lecture 16 Module Creations And Usage
Lecture 17 Package Creation And Importing
Section 7: NumPy Library
Lecture 18 Introduction To NumPy Library
Section 8: Pandas For Data Science And Machine Learning
Lecture 19 Playing With Pandas - Part 1
Lecture 20 Playing With Pandas - Part 2
Lecture 21 Basic Statistics And Data Visualization Using Python
Section 9: Introduction To Machine Learning
Lecture 22 Machine Learning Overview
Lecture 23 Supervised And Unsupervised Learning
Section 10: Implementing Regression Analysis
Lecture 24 Linear Regression With Python
Lecture 25 Logistic Regression With Python
Section 11: Implementing Decision Tree
Lecture 26 Overview Of Decision Tree
Lecture 27 Decision Tree With Python - Part 1
Lecture 28 Decision Tree With Python - Part 2
Lecture 29 Decision Tree With Python - Part 3
Lecture 30 Decision Tree With Python - Part 4
Lecture 31 Decision Tree With Python - Part 5
Section 12: Implementing Regression Tree
Lecture 32 Regression Tree With Python
Section 13: Implementing Random Forest
Lecture 33 Random Forest With Python - Part 1
Lecture 34 Random Forest With Python - Part 2
Section 14: Implementing SVM - Support Vector Machines
Lecture 35 Support Vector Machines With Python
Section 15: Implementing K-nearest Neighbor
Lecture 36 How To Calculate Euclidean Distance
Lecture 37 Understanding KNN Algorithm
Lecture 38 K-nearest Neighbor or KNN Algorithm
Section 16: Implementing Naïve Bayes Classifier
Lecture 39 Naïve Bayes Classifier With Python
Section 17: Implementing K-means Clustering
Lecture 40 K-means Clustering With Python
Section 18: Hierarchical Clustering
Lecture 41 Hierarchical Clustering - Part 1
Lecture 42 Hierarchical Clustering With Case Studies
Lecture 43 Hierarchical Clustering - Part 2
Lecture 44 Hierarchical Clustering - Part 3
Section 19: DIY - Build Your Own Credit Risk Analyzer
Lecture 45 Understanding Credit Risk Analyzer
Lecture 46 Building A Credit Risk Analyzer
Lecture 47 Build Your Own Credit Risk Analyzer
Anyone who is serious about learning machine learning, data science techniques and looking forward to a rewarding career in Machine Learning


Homepage

https://www.udemy.com/course/python-for-machine-learning-with-solved-projects-by-spotle/