Data Science and Machine Learning with Python Part I

This course will help you learn the fundamentals. It is aimed for complete beginners. You can expect to learn few tips to work quickly and efficiently with technologies like HTML, CSS and Python. This is course is divided into three parts for your convenience. Finish all the three parts to learn the fundamentals of all the development technologies.

Coupon code - WIISEGT

It is available for all the learners.

WIISE

The outline of this course is mentioned below:

Getting Started:

• Introduction
• Getting What You Need
• Installing Enthought Canopy
• Python Basics, Part 1
• Python Basics, Part 2
• Running Python Scripts
• Introducing the Pandas Library

Statistics and Probability Refresher, and Python Practise:

• Types of Data
• Mean, Median, Mode
• Using mean, median, and mode in Python
• Variation and Standard Deviation
• Probability Density Function; Probability Mass Function
• Common Data Distributions
• Percentiles and Moments
• A Crash Course in matplotlib
• Covariance and Correlation
• Conditional Probability
• Bayes' Theorem

Predictive Models:

• Linear Regression
• Polynomial Regression
• Multivariate Regression, and Predicting Car Prices
• Multi-Level Models

Machine Learning with Python:

• Supervised vs. Unsupervised Learning, and Train/Test
• Using Train/Test to Prevent Overfitting a Polynomial Regression
• Bayesian Methods: Concepts
• Implementing a Spam Classifier with Naive Bayes
• K-Means Clustering
• Clustering people based on income and age
• Measuring Entropy
• Decision Trees: Concepts
• Decision Trees: Predicting Hiring Decisions
• Ensemble Learning
• Support Vector Machines (SVM) Overview
• Using SVM to cluster people using scikit-learn

Recommender Systems:

• User-Based Collaborative Filtering
• Item-Based Collaborative Filtering
• Finding Movie Similarities
• Improving the Results of Movie Similarities
• Making Movie Recommendations to People
• Improve the recommender's results

More Data Mining and Machine Learning Techniques:

• K-Nearest-Neighbors: Concepts
• Using KNN to predict a rating for a movie
• Dimensionality Reduction; Principal Component Analysis
• PCA Example with the Iris data set
• Data Warehousing Overview: ETL and ELT
• Reinforcement Learning

WIISE is a 'Professional Learning Network'​ with a global outreach that helps anyone to learn anything to achieve personal and professional goals.

We bring top-rated interactive learning courses & certifications from across the world through respected Global Academic Institutes and Industry experts to our learners.

WIISE for Teams is a Smart training solution suitable for growing businesses (SMB’s) - deliver online cost-effective, on-demand training, staff engagement & Upskilling to their employees and customers. WIISE incorporates the latest micro-learning & social-learning techniques that provides fast and engaging training at a fraction of cost of traditional training methods.

WIISE is brought by respectable Learning services & Skill development company - PositiveShift Group - Silicon Valley CA USA, India (www.positiveshift.in). The company has been awarded unique Innovation partnership with National Skill Development Corporation (NSDC) and Ministry of Skill Development and Entrepreneurship, Govt of India.