Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 48000 Hz, 2ch | Size: 4.36 GB
Genre: eLearning Video | Duration: 16 lectures (6 hour, 49 mins) | Language: English
A beginners guide to learn Machine Learning from scratch. Learn various algorithms and techniques using ML libraries.
What you'll learn Homepage: https://www.udemy.com/course/step-by-step-guide-to-machine-learning-course/
Learn how to use NumPy to do fast mathematical calculations
Learn what is Machine Learning and Data Wrangling
Learn how to use scikit-learn for data-preprocessing
Learn different model selection and feature selections techniques
Learn about cluster analysis and anomaly detection
Learn about SVMs for classification, regression and outliers detection.
Requirements
Basic knowledge of scripting and programming
Basic knowledge of python programming
Description
If you are looking to start your career in machine learning then this is the course for you.
This is a course designed in such a way that you will learn all the concepts of machine learning right from basic to advanced levels.
This course has 5 parts as given below:
Introduction to Machine Learning & Data Wrangling
Linear Models, Trees & Preprocessing
Model Evaluation, Feature Selection & Pipelining
Bayes, Nearest Neighbours & Clustering
SVM, Anomalies, Imbalanced Classes, Ensemble Methods
For the code explained in each lecture, you can find a GitHub link in the resources section.
Who this course is for:
Beginners who want to become a data scientist
Software developers who want to learn machine learning from scratch
Python developers who are interested to learn machine learning
Professionals who want to start their career in Machine Leaning
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