Complete Machine Learning & Data Science with Python| ML A-Z

Artificial Intelligence is the next digital frontier, with profound implications for business and society. The global AI market size is projected to reach $202.57 billion by 2026, according to Fortune Business Insights.This Data Science & Machine Learning (ML) course is not only ‘Hands-On’ practical based but also includes several use cases so that students can understand actual Industrial requirements, and work culture. These are the requirements to develop any high level application in AI. In this course several Machine Learning (ML) projects are included.1) Project - Customer Segmentation Using K Means Clustering2) Project - Fake News Detection using Machine Learning (Python)3) Project COVID-19: Coronavirus Infection Probability using Machine Learning4) Project - Image compression using K-means clustering | Color Quantization using K-Means This course include topics ---What is Data Science Describe Artificial Intelligence and Machine Learning and Deep Learning Concept of Machine Learning - Supervised Machine Learning , Unsupervised Machine Learning and Reinforcement Learning Python for Data Analysis- Numpy Working envirnment-Google Colab Anaconda Installation Jupyter Notebook Data analysis-Pandas Matplotlib What is Supervised Machine Learning Regression Classification Multilinear Regression Use Case- Boston Housing Price Prediction Save Model Logistic Regression on Iris Flower Dataset Naive Bayes Classifier on Wine Dataset Naive Bayes Classifier for Text Classification Decision TreeK-Nearest Neighbor(KNN) Algorithm Support Vector Machine Algor