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Python for Data Science and Machine Learning

LIVE
60 Hours

Course offered by Nishank Yadav

2 reviews

Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more!

What You will Learn

Use Python for Data Science and Machine Learning

  • Use Spark for Big Data Analysis
  • Implement Machine Learning Algorithms
  • Learn to use NumPy for Numerical Data
  • Learn to use Pandas for Data Analysis
  • Learn to use Matplotlib for Python Plotting
  • Learn to use Seaborn for statistical plots
  • Use Plotly for interactive dynamic visualizations
  • Use SciKit-Learn for Machine Learning Tasks
  • K-Means Clustering
  • Logistic Regression
  • Linear Regression
  • Random Forest and Decision Trees
  • Natural Language Processing and Spam Filters
  • Neural Networks
  • Support Vector Machines
Syllabus / Course content

Environment Set-Up1 lecture

  • Python Environment Setup

Jupyter Overview

  • Updates to Notebook Zip
  • Jupyter Notebooks
  • Optional: Virtual Environments

Python Crash Course

  • Welcome to the Python Crash Course Section!
  • Introduction to Python Crash Course
  • Python Crash Course
  • Python Crash Course Exercises - Overview
  • Python Crash Course Exercises - Solutions

Python for Data Analysis - NumPy

  • Welcome to the NumPy Section!

Just a quick introduction of the section from me personally!

  • Introduction to Numpy

Part of the NumPy Section of the Course!

  • Numpy Arrays

Part of the NumPy Section of the Course!

  • Quick Note on Array Indexing
  • Numpy Array Indexing
  • Numpy Operations
  • Numpy Exercises Overview
  • Numpy Exercises Solutions

Python for Data Analysis - Pandas

  • Welcome to the Pandas Section!
  • Introduction to Pandas
  • Series
  • DataFrames - Part 1
  • DataFrames - Part 2
  • DataFrames - Part 3
  • Missing Data
  • Groupby
  • Merging Joining and Concatenating
  • Operations
  • Data Input and Output

Python for Data Analysis - Pandas Exercises

  • Note on SF Salary Exercise
  • SF Salaries Exercise Overview
  • SF Salaries Solutions
  • Ecommerce Purchases Exercise Overview
  • Ecommerce Purchases Exercise Solutions

 

Python for Data Visualization - Matplotlib

  • Welcome to the Data Visualization Section!

Preview

  • Introduction to Matplotlib

Preview

  • Matplotlib Part 1
  • Matplotlib Part 2
  • Matplotlib Part 3
  • Matplotlib Exercises Overview
  • Matplotlib Exercises - Solutions

Python for Data Visualization - Seaborn

  • Introduction to Seaborn
  • Distribution Plots

Preview

  • Categorical Plots
  • Matrix Plots
  • Grids
  • Regression Plots
  • Style and Color
  • Seaborn Exercise Overview
  • Seaborn Exercise Solutions

Python for Data Visualization - Pandas Built-in Data Visualization

  • Pandas Built-in Data Visualization
  • Pandas Data Visualization Exercise
  • Pandas Data Visualization Exercise- Solutions

Python for Data Visualization - Plotly and Cufflinks

  • Introduction to Plotly and Cufflinks

Preview

  • READ ME FIRST BEFORE PLOTLY PLEASE!
  • Plotly and Cufflinks

Python for Data Visualization - Geographical Plotting

  • Introduction to Geographical Plotting

Preview

  • Choropleth Maps - Part 1 - USA
  • Choropleth Maps - Part 2 - World
  • Choropleth Exercises
  • Choropleth Exercises - Solutions

Data Capstone Project

  • Welcome to the Data Capstone Projects!

Preview

  • 911 Calls Project Overview

Preview

  • 911 Calls Solutions
  • Bank Data
  • Finance Data Project Overview
  • Finance Project - Solutions

Introduction to Machine Learning

  • Welcome to Machine Learning. Here are a few resources to get you started!
  • Welcome to the Machine Learning Section!
  • Supervised Learning Overview
  • Evaluating Performance - Classification Error Metrics
  • Evaluating Performance - Regression Error Metrics
  • Machine Learning with Python

Linear Regression

  • Linear Regression Theory
  • model_selection Updates for SciKit Learn 0.18
  • Linear Regression with Python
  • Linear Regression Project Overview
  • Linear Regression Project Solution

Cross Validation and Bias-Variance Trade-Off

  • Bias Variance Trade-Off

Logistic Regression

  • Logistic Regression Theory
  • Logistic Regression with Python
  • Logistic Regression Project Overview
  • Logistic Regression Project Solutions

K Nearest Neighbors

  • KNN Theory
  • KNN with Python
  • KNN Project Overview
  • KNN Project Solutions

Decision Trees and Random Forests

  • Introduction to Tree Methods
  • Decision Trees and Random Forest with Python
  • Decision Trees and Random Forest Project Overview
  • Decision Trees and Random Forest Solutions

Support Vector Machines

  • SVM Theory
  • Support Vector Machines with Python
  • SVM Project Overview
  • SVM Project Solutions

K Means Clustering

  • K Means Algorithm Theory
  • K Means with Python
  • K Means Project Overview
  • K Means Project Solutions

Principal Component Analysis

  • Principal Component Analysis
  • PCA with Python

Recommender Systems

  • Recommender Systems
  • Recommender Systems with Python

Natural Language Processing

  • Natural Language Processing Theory
  • NLP with Python
  • NLP Project Overview
  • NLP Project Solutions

Neural Nets and Deep Learning

  • Deep Learning Section!
  • Introduction to Artificial Neural Networks (ANN)
  • Installing TensorFlow
  • Perceptron Model
  • Neural Networks
  • Activation Functions
  • Multi-Class Classification Considerations
  • Cost Functions and Gradient Descent
  • Backpropagation
  • TensorFlow vs Keras
  • TF Syntax Basics - Part One - Preparing the Data
  • TF Syntax Basics - Part Two - Creating and Training the Model
  • TF Syntax Basics - Part Three - Model Evaluation
  • TF Regression Code Along - Exploratory Data Analysis
  • TF Regression Code Along - Data Preprocessing and Creating a Model
  • TF Regression Code Along - Model Evaluation and Predictions
  • TF Classification Code Along - EDA and Preprocessing
  • TF Classification - Dealing with Overfitting and Evaluation
  • TensorFlow 2.0 Project Options Overview
  • TensorFlow 2.0 Project Notebook Overview
  • Keras Project Solutions - Dealing with Missing Data
  • Keras Project Solutions - Categorical Data
  • Keras Project Solutions - Data PreProcessing
  • Keras Project Solutions - Creating and Training a Model
  • Keras Project Solutions - Model Evaluation
  • Tensorboard

Big Data and Spark with Python

  • Welcome to the Big Data Section!
  • Big Data Overview
  • Spark Overview
  • Local Spark Set-Up
  • AWS Account Set-Up
  • Quick Note on AWS Security
  • EC2 Instance Set-Up
  • SSH with Mac or Linux
  • PySpark Setup
  • Lambda Expressions Review
  • Introduction to Spark and Python
  • RDD Transformations and Actions

About the Trainer

Sandeep picture

5 Avg Rating

2 Reviews

2 Students

2 Courses

Nishank Yadav

Master's in Technology

6 Years of Experience

7+ years of experience in MNCs of working in various analytical teams.

Hands on experience in to marketing analytics,, Credit Risk Models.

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