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

Learn Numpy, Pandas, Matplotlib, Seaborn, Scipy, Supervised & Unsupervised Machine Learning A-Z and feature engineering

Bullstrack Bullstrack
May 30, 2023 - 17:57 Updated: May 17, 2023 - 22:46
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Complete Machine Learning & Data Science with Python| ML A-Z
Complete Machine Learning & Data Science with Python| ML A-Z

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

Learn Numpy, Pandas, Matplotlib, Seaborn, Scipy, Supervised & Unsupervised Machine Learning A-Z and feature engineering

What you'll learn:

Machine Learning, Data Science and Deep Learning with Python

  • Build artificial neural networks with Tensorflow and Keras
  • Implement machine learning at a massive scale with Apache Spark’s MLLib
  • Classify images, data, and sentiments using deep learning
  • Make predictions using linear regression, polynomial regression, and multivariate regression
  • Data Visualization with Matplotlib and Seaborn
  • Understand reinforcement learning – and how to build a Pac-Man bot
  • Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA
  • Use train/test and K-Fold cross-validation to choose and tune your models
  • Build a movie recommender system using item-based and user-based collaborative filtering
  • Clean your input data to remove outliers
  • Design and evaluate A/B tests using T-Tests and P-Values

Requirements:

  • You’ll need a desktop computer (Windows, Mac, or Linux) capable of running Anaconda 3 or newer. The course will walk you through installing the necessary free software.
  • Some prior coding or scripting experience is required.
  • At least high school-level math skills will be required.

Description:

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 Clustering

2) Project - Fake News Detection using Machine Learning (Python)

3) Project COVID-19: Coronavirus Infection Probability using Machine Learning

4) 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 Tree

  • K-Nearest Neighbor(KNN) Algorithm

  • Support Vector Machine Algorithm

  • Random Forest Algorithm I

  • What is UnSupervised Machine Learning

  • Types of Unsupervised Learning

  • Advantages and Disadvantages of Unsupervised Learning

  • What is clustering?

  • K-means Clustering

  • Image compression using K-means clustering | Color Quantization using K-Means

  • Underfitting, Over-fitting and best fitting in Machine Learning

  • How to avoid Overfitting in Machine Learning

  • Feature Engineering

  • Teachable Machine

  • Python Basics

In the recent years, self-driving vehicles, digital assistants, robotic factory staff, and smart cities have proven that intelligent machines are possible. AI has transformed most industry sectors like retail, manufacturing, finance, healthcare, and media and continues to invade new territories. Everyday a new app, product or service unveils that it is using machine learning to get smarter and better.

NOTE :- In description reference notes also provided , open reference notes , there is Download link. You can download datasets there.

Who this course is for:

Course Details:

  • 11 hours on-demand video
  • 29 downloadable resources
  • Access on mobile and TV
  • Full lifetime access
  • Certificate of completion

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

Learn Numpy, Pandas, Matplotlib, Seaborn, Scipy, Supervised & Unsupervised Machine Learning A-Z and feature engineering

Demo Link: https://www.udemy.com/course/complete-machine-learning-data-science-libraries-with-python/

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