MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 34 lectures (5h 7m) | Size: 2.44 GB
Learn R, Python, Machine Learning, Deep Learning, Google Colab, Real world projects with Code and step by step guidance
What you'll learn:
Why we need Data Mining & Machine Learning
What is Data Mining
What is Machine Learning
Traditional Programming Vs Machine Learning
Steps to Solve a Data Mining & Machine Learning Problem
Types of Learning in Machine learning (Supervised, Unsupervised, Reinforcement )
Classification & Clustering
Setting up the Environment for Machine Learning - R language and R studio , Python, Anaconda
Introduction to Deep Learning - Guest Lecture
Machine learning project : Car Price Prediction Project
Kaggle - Covid 19- Classification (Chest X-ray.) - Covid-19 & Pneumonia
Supervised Learning
Unsupervised Learning
Requirements
Computer with Internet connection
Python or any programming language
Description
Academy of Computing & Artificial Intelligence proudly present you the course "Data Engineering with Python". It all started when the expert team of Academy of Computing & Artificial Intelligence (PhD, PhD Candidates, Senior Lecturers , Consultants , Researchers) and Industry Experts . hiring managers were having a discussion on the most highly paid jobs & skills in the IT/Computer Science / Engineering / Data Science sector in 2021.
At the end of the Course you will be able to start your career in Data Mining & Machine Learning.
1) Introduction to Machine Learning - [A -Z] Comprehensive Training with Step by step guidance
2) Setting up the Environment for Machine Learning - Step by step guidance [R Programming & Python]
3) Supervised Learning - (Univariate Linear regression, Multivariate Linear Regression, Logistic regression, Naive Bayes Classifier, Trees, Support Vector Machines (SVM), Random Forest)
4) Unsupervised Learning
5) Convolutional Neural Networks - CNN
6) Artificial Neural Networks
7) Real World Projects with Source
Course Learning Outcomes
To provide awareness of (Supervised & Unsupervised learning) coming under Machine Learning (Why we need Data Mining & Machine Learning, What is Data Mining, What is Machine Learning, Traditional Programming Vs Machine Learning, Steps to Solve a Data Mining & Machine Learning Problem, Classification , Clustering)
Describe intelligent problem-solving methods via appropriate usage of Machine Learning techniques.
To build appropriate neural models from using state-of-the-art python framework.
To setup the Environment for Machine Learning - Step by step guidance [R Programming & Python]
Convolutional Neural Networks - CNN
Resources from MIT and many famous Universities
Projects with Source
Who this course is for
Anyone who wish to start the career in Data Science & Machine Learning
Homepage
https://www.udemy.com/course/machine-le … h-r-python
Screenshots
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