Home > Courses > Data Science > Development > Python Machine Learning : Learn Handson™
   3.9  31 reviews on Udemy

Python Machine Learning : Learn Handson™

Naive Bayes Classifier, Decision tree, PCA, kNN classifier, linear regression, logistic regression,SVM classifier
Course from Udemy
 877 students enrolled
 en
Linear Regression, SVR, Decision Tree Regression, Random Forest Regression
Machine Learning, Deep Learning, AI and Data Science Basic Concepts
Python package “Numpy” for numerical computation, Python package “Matplotlib” for visualization and plotting, Python package “pandas” for data analysis
Polynomial Regression
Logistic Regression
K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification
Random Forest Classification
Clustering: K-Means, Hierarchical Clustering
Data Visualization in Python with MatPlotLib and Seaborn
Dimensionality Reduction: PCA, PCA sklearn
Supervised Learning & Unsupervised Learning
Support Vector Machine
Curse of Dimensionality
Neural Networks
Applications of ML/AI/DS and Job prospects
K-Nearest Neighbour Classifier, Naïve Bayes Classifier, Decision Tree Classifier, Support Vector Machine Classifier, Random Forest Classifier (We shall use Python built-in libraries to solve classification problems using above mentioned classification algorithms)
Linear Algebra Review: Eigen value decomposition.
Multi-layered Perceptron (MLP) and its architecture.
Learning Rule : Back-Propagation
High dimensionality in data set and its problems.
Environment Setup : Anaconda and Jupyter Notebook
Using in-built Python libraries for solving linear regression problem.
Python implementation of Gradient Descent update rule for logistic regression.

Learn to use Python, the ideal programming language for Machine Learning, with this comprehensive course from Hands-On System. Python plays an important role in the adoption of Machine Learning (ML) in the business environment.

Now a day’s Machine Learning is one of the most sought-after skills in the industry. After completion of this course, students will understand and apply the concepts of machine learning and applied statistics for real-world problems.

The topics we will be covering in this course are Python libraries for data manipulation and visualization such as NumPy, matplotlib, and pandas. Linear Algebra, Exploratory Data Analysis, Linear Regression, Various Classification Techniques, Clustering, Dimensionality reduction, and Artificial Neural Networks.

This course is designed for students who are pursuing a bachelor’s or master’s degree in Statistics, Mathematics, Computer Science, Economics or any engineering field. The students should have a little bit of knowledge in coding and undergraduate-level mathematics.

Terminal competencies of the course, one would have learnt about tools to train machines based on real-world situations using Machine Learning algorithms, as well as to create complex algorithms and neural networks. During the latter stage of the course, learners will be introduced to real-world use cases of Machine Learning with Python for a Hands-On learning experience which would prepare them to create applications efficiently.


Python Machine Learning : Learn Handson™
$ 94.99
per course
Also check at

FAQs About "Python Machine Learning : Learn Handson™"

About

Elektev is on a mission to organize educational content on the Internet and make it easily accessible. Elektev provides users with online course details, reviews and prices on courses aggregated from multiple online education providers.
DISCLOSURE: This page may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission.

CONTACT

[email protected]

SOCIAL NETWORK

Copyright © Elektev
Privacy Policy