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The #1 Python Data Scientist: Sentiment Analysis & More

Name: The #1 Python Data Scientist: Sentiment Analysis & More
Rating: 4.5 (28 reviews)

Build Projects with Machine Learning, Text Classification, TensorFlowNumPy, PyPlot, Pandas, and More in Google Colab...

Created byMammoth Interactive, John Bura

Last updated 5/2020

English

What you'll learn

Process text data
Interpret sentiment in reviews
Build a model to predict whether a review is positive or negative
Implement logic
Track data
Customize graphs
Implement responsiveness
Build data structures
Graph data with PyPlot
Build 3D graphs with PyPlot
Use common array functions
Replace Python lists with NumPy arrays
Build and use NumPy arrays
Use Pandas series
Use Pandas Date Ranges
Read CSVs with Pandas
Use Pandas DataFrames
Get elements from a Series
Get properties from a series
Series operations
Modify series
Series comparisons and iteration
Series operations
And much more!

Course content

7 sections • 105 lectures • 16h 37m total length

Learn Python for Beginners Overview4:47
Introduction to Python5:46
Variables19:34
Type Conversion Examples10:21
Operators7:21
Operators Examples22:09
Collections8:39
Explore Python collections by examining lists, tuples, dictionaries, and ranges, and learn how indices, mutability, and keys shape data storage and retrieval.
Lists11:55
Multidimensional List Examples8:22
Tuples Examples8:51
Dictionaries Examples14:41
Ranges Examples8:47
Conditionals6:58
If Statements Examples10:32
If Statements Variants Examples11:35
Loops7:17
While Loops Examples11:47
For Loops Examples11:35
Functions8:04
Master Python functions as self-contained blocks of code that execute when called, and learn to use parameters, return values, and default values for flexible reuse.
Functions Examples9:33
Parameters And Return Values Examples14:08
Classes and Objects11:30
Explore how classes define blueprints for objects, encapsulating state with fields and behavior with methods, and how instantiation creates objects. Learn inheritance and static members that share data across instances.
Classes Examples13:28
Explore building a custom Python class for a player character, including attributes, a constructor that initializes with self, and methods like move, take damage, and is dead.
Objects Examples10:11
Inheritance Examples17:43
Static Members Examples11:20
Summary and Outro4:23
Python PDF Resource0:01
Source Code ($150 Value)

Learn NumPy for Beginners Course Overview5:11
Intro to NumPy6:20
Explore NumPy, a Python library that provides fast, powerful arrays with a C backend, supporting data science, machine learning, web services with Flask, and conversions with pandas.
Installing NumPy3:59
Creating NumPy Arrays16:55
Explore creating one-dimensional numpy arrays by converting a Python list with np.array, and by building zeros, ones, and empty arrays; compare arange and linspace for ranges and spacing.
Creating NumPy Matrices11:57
Getting and Setting NumPy Elements16:59
Arithmetic Operations on NumPy Arrays11:56
NumPy Functions Part 119:13
NumPy Functions Part 212:36
Explore numpy built-in functions to retrieve array properties and modify arrays, including max, min, mean, argmax, argmin, and non-zero indices, plus sort, flip, transpose, and flatten for arrays and matrices.
Summary and Outro3:01
Explore numpy basics, from creating arrays from lists and dictionaries to indexing, properties, and one-dimensional and multi-dimensional operations, plus using built-in functions and future learning paths.
Source Code ($150 Value)
Numpy PDF Resource0:01

Learn Pandas for Beginners Course Overview5:43
Intro to Pandas7:55
Installing Pandas5:28
Creating Pandas Series20:34
Date Ranges11:29
Getting Elements from Series19:21
Retrieve single elements from a pandas series by position or label, then slice for multiple elements. Filter with boolean tests and use series.get for safe defaults.
Getting Properties of Series13:04
Modifying Series19:01
Operations on Series11:48
Creating Pandas DataFrames22:57
Getting Elements from DataFrames25:12
Getting Properties from DataFrames17:44
Dataframe Modification36:24
DataFrame Operations20:09
DataFrame Comparisons and Iteration15:35
Reading CSVs12:00
Summary and Outro4:14
Pandas PDF Resource0:01
Source Code ($150 Value)

Machine Learning for Beginners Course Overview6:05
Machine Learning Overview9:01
Deep Dive into Machine Learning6:01
Problems Solved with Machine Learning Part 113:26
Problems Solved with Machine Learning Part 216:25
Types of Machine Learning10:15
How Machine Learning Works11:40
Common Machine Learning Structures13:51
Steps to Build a Machine Learning Program16:34
Summary and Outro2:49
Machine Learning PDF Resource0:01

Learn TensorFlow for Beginners Overview6:10
Intro to Tensorflow5:33
Installing Tensorflow3:52
Intro to Linear Regression9:26
Linear Regression Model - Creating Dataset5:49
Linear Regression Model - Building the Model7:22
Linear Regression Model - Creating a Loss Function5:57
Linear Regression Model - Training the Model12:42
Linear Regression Model - Testing the Model5:22
Summary and Outro2:55
Explore how to use TensorFlow to build, train, and test a simple linear regression model, implement gradient descent, and evaluate performance with loss metrics.
TensorFlow PDF Resource0:01
Source Code ($150 Value)

Sentiment Analysis Project Overview6:19
How Machines Interpret Text15:23
Building the Model Part 1 - Examining Dataset12:27
Building the Model Part 2 - Formatting Dataset15:14
Building the Model Part 3 - Building the Model10:30
Building the Model Part 4 - Training the Model5:42
Building the Model Part 5 - Testing the Model9:26
Course Summary and Outro3:29
Source Code ($150 Value)
Sentiment Analysis PDF Resource0:01

Requirements

No OS requirement but the tutorials are recorded on a Mac with Google Colab
No experience necessary

Description

Learn everything you need to become a data scientist.

Machine learning is quickly becoming a required skill for every software developer.

Enroll now to learn everything you need to know to get up to speed, whether you're a developer or aspiring data scientist. This is the course for you.

Your complete Python course for image recognition, data analysis, data visualization and more.

Reviews On Our Python Courses:

"I know enough Python to be dangerous. Most of the ML classes are so abstract and theoretical that no learning happens. This is the first class where we use concrete examples that I can relate to and allow me to learn. Absolutely love this course!" - Mary T.
"Yes, this is an amazing start. For someone new in python this is a very simple boot course. I am able to relate to my earlier programming experience with ease!" - Gajendran C.
"Clear and concise information" - Paul B.
"Easy to understand and very clear explanations. So far so good!!!" - Alejandro M.

This is a once in a lifetime chance to enroll in a massive course.

Absolutely no experience necessary. Start with a complete introduction to Python that is perfect for absolute beginners and can also be used a review.

Jump into using the most popular libraries and frameworks for working with Python. You'll learn everything you need to become a data scientist. This includes:

0. Python Crash Course for Beginners

Learn Python with project based examples. Get up and running even if you have no programming experience. Superboost your career by masterig the core Python fundamentals.

1. Data Science with NumPy

Build projects with NumPy, the #1 Python library for data science providing arrays and matrices.

2. Data Analysis with Pandas

Build projects with pandas, a software library written for the Python programming language for data manipulation and analysis.

2. Data Visualization with PyPlot

Build projects with pyplot, a MATLAB-like plotting framework enabling you to create a figure, create a plotting area in a figure, plot lines in a plotting area, decorate the plot with labels and much more. Learn it all in this massive course.

3. Machine Learning Theory

Machine learning is in high demand and is quickly becoming a requirement on every software engineer's resume. Learn how to solve problems with machine learning before diving into practical examples.

4. Introduction to TensorFlow

Build projects with TensorFlow, the most popular platform enabling ML developers to build and deploy machine learning applications such as neural networks. Build your first linear regression model with TensorFlow. Learn how to build a dataset, model, train and test!

5. Build a Sentiment Analysis Model to Classify Reviews as Positive or Negative

All source code is included for each project.

If you buy one course this year, this is it. Sign up while spots are open.

Who this course is for:

Anyone who needs to learn sentiment analysis and more
Anyone who needs to learn Python
Anyone who needs to know more about machine learning
Anyone who needs to graph with Python
Anyone with no Python experience
Anyone who needs an efficient way to analyze data
Anyone with little to no programming experience
Anyone who wants to use efficient arrays
Anyone with little to no knowledge of machine learning

The #1 Python Data Scientist: Sentiment Analysis & More

What you'll learn

Explore related topics

Course content

Learn Python for Beginners29 lectures • 4hr 51min

Learn NumPy for Beginners Course12 lectures • 1hr 48min

Learn Pandas for Beginners Course19 lectures • 4hr 29min

Learn pyplot for Beginners Course12 lectures • 1hr 20min

Machine Learning for Beginners Course11 lectures • 1hr 46min

Learn TensorFlow for Beginners12 lectures • 1hr 5min

Sentiment Analysis Project: Classify Positive/Negative Reviews10 lectures • 1hr 19min

Requirements

Description

Who this course is for: