The #1 Python Data Scientist: Sentiment Analysis & More
- 4.7
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Brief Introduction
Build Projects with Machine Learning, Text Classification, TensorFlowNumPy, PyPlot, Pandas, and More in Google Colab...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.
Requirements
- Requirements
- No OS requirement but the tutorials are recorded on a Mac with Google Colab
- No experience necessary
Knowledge
- 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!
Mammoth Interactive
4.7 Raiting
The #1 Python Data Scientist: Sentiment Analysis & More
- 4.7
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Build Projects with Machine Learning, Text Classification, TensorFlowNumPy, PyPlot, Pandas, and More in Google Colab. . . Learn everything you need to become a data scientist....
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Lay the Foundation: Insights & Corporate Roles, Discrete & Continuous random variables, Descriptive Stats & Percentile! ” - Josh Wills Statistics for Data Science...
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- 4.4
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This course introduces the concepts of Artificial Intelligence and Machine learning. We'll discuss machine learning types and tasks, and machine learning algorithms....
