Data Wrangling in Pandas for Machine Learning Engineers
Data Wrangling in Pandas for Machine Learning Engineers, available at $44.99, has an average rating of 4.25, with 89 lectures, 7 quizzes, based on 118 reviews, and has 806 subscribers.
You will learn about You'll learn data wrangling in Python. You'll be prepared for interview questions on data wrangling in Python. Data wrangling is what machine learning engineers do around 70% of the time and the skills in this course will put you ahead of others in the real world. You'll be adept using the most important Python library for data wrangling. This course is ideal for individuals who are If you're interested in becoming a machine learning engineer then this course is for you. or If you're interested in becoming a data engineer then this course is for you. or If you're a professional in any discipline that needs to become adept at data wrangling then this course is for you. It is particularly useful for If you're interested in becoming a machine learning engineer then this course is for you. or If you're interested in becoming a data engineer then this course is for you. or If you're a professional in any discipline that needs to become adept at data wrangling then this course is for you.
Enroll now: Data Wrangling in Pandas for Machine Learning Engineers
Summary
Title: Data Wrangling in Pandas for Machine Learning Engineers
Price: $44.99
Average Rating: 4.25
Number of Lectures: 89
Number of Quizzes: 7
Number of Published Lectures: 89
Number of Published Quizzes: 7
Number of Curriculum Items: 96
Number of Published Curriculum Objects: 96
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- You'll learn data wrangling in Python.
- You'll be prepared for interview questions on data wrangling in Python.
- Data wrangling is what machine learning engineers do around 70% of the time and the skills in this course will put you ahead of others in the real world.
- You'll be adept using the most important Python library for data wrangling.
Who Should Attend
- If you're interested in becoming a machine learning engineer then this course is for you.
- If you're interested in becoming a data engineer then this course is for you.
- If you're a professional in any discipline that needs to become adept at data wrangling then this course is for you.
Target Audiences
- If you're interested in becoming a machine learning engineer then this course is for you.
- If you're interested in becoming a data engineer then this course is for you.
- If you're a professional in any discipline that needs to become adept at data wrangling then this course is for you.
Reviews:
The examples given and explanation provided by the instructor were great. He is entertaining as well as knowledgeable about the subject. – Prakash Shelke
Spectacular step by step instructions with great examples and labs. -Donato
Great course !!!!! You learn how to use the Pandas library for its own sake and not as a part of some courses devoted to other topics. -Giovanni De Angelis
The course is really impressive. Tons of information, and I learned a great deal. I had no Python background, and now I feel a lot more confident about working with Python than ever. Thanks for the course. Austin
Honestly Mike your classes speak for themselves. They’re informative, concise and just really well put together. They’re exactly the kind of courses I look for. –Alex El
I have been a software engineer for more years than I care to admit. I found the presentation, speed and depth fit what I was looking for perfectly. I believe at this point I understand enough about Pandas so that I can move forward with this branch of learning. – Danny
Course Description
Welcome to Data Wrangling in Pandas for Machine Learning Engineers
This is the second course in a series designed to prepare you for becoming a machine learning engineer.
I’ll keep this updated and list only the courses that are live. Here is a list of the courses that can be taken right now. Please take them in order. The knowledge builds from course to course.
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The Complete Python Course for Machine Learning Engineers
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Data Wrangling in Pandas for Machine Learning Engineers (This one)
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Data Visualization in Python for Machine Learning Engineers
Learn the single most important skill for the machine learning engineer: Data Wrangling
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A complete understanding of data wrangling vernacular.
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Pandas from A-Z.
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The ability to completely cleanse a tabular data set in Pandas.
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Lab integrated. Please don’t just watch. Learning is an interactive event. Go over every lab in detail.
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Real world Interviews Questions.
The knowledge buildsfrom course to course in a serial nature. Withoutthe first course many students might struggle with this one. Thank you.
Many new to machine learning believe machine learning engineers spend their days building deep
neural models in Keras or SciKit-Learn. I hate to be the bearer of bad news but that isn’t the case.
A recent study from Kaggle determined that 80% of time data scientists and machine learning engineers
spend their time cleaning data. The term used for cleaning data in data science circles is called data wrangling.
In this course we are going to learn Pandasusing a lab integrated approach. Programming is something you have to do in
order to master it. You can’t read about Python and expect to learn it.
Pandas is the single most important library for data wrangling in Python.
Data wrangling is the process of programmatically transforming data into a format that makes it easier to work with.
This might mean modifying all of the values in a given column in a certain way, or merging multiple columnstogether. The necessity for data wrangling is often a byproduct of poorly collected or presented data.
In the real world data is messy. Very rarelydo you have nicely cleansed data setsto point your supervised models against.
Keep in mind that 99% of all applied machine learning (real world machine learning) is supervised.That simply means models need really clean, nicely formatted data. Bad data in means bad model results out.
**Five Reasons to Take this Course**
1) You Want to be a Machine Learning Engineer
It’s one of the most sought after careers in the world. The growth potential career wise is second to none. You want the freedom to move anywhere you’d like. You want to be compensated for your efforts. You want to be able to work remotely. The list of benefits goes on. Without a solid understanding of data wrangling in Python you’ll have a hard time of securing a position as a machine learning engineer.
2) Most of Machine Learning is Data Wrangling
If you’re new to this space the one thing many won’t tell you is that much of the job of the data scientist and the machine learning engineer is massaging dirty data into a state where it can be modeled. In the real world data is dirty and before you can build accurate machine learning models you have to clean it. This process is called data wrangling and without this skills set you’ll never get a job as a machine learning engineer. This course will give you the fundamentals you need to cleanse your data.
3) The Growth of Data is Insane
Ninety percent of all the world’s data has been created in the last two years. Business around the world generate approximately 450 billion transactions a day. The amount of data collected by all organizations is approximately 2.5 exabytes a day. That number doubles every month. Almost all real world machine learning is supervised. That means you point your machine learning models at clean tabular data. Python has libraries that are specific to data cleansing.
4) Machine Learning in Plain English
Machine learning is one of the hottest careers on the planet and understanding the basics is required to attaining a job as a data engineer. Google expects data engineers and their machine learning engineers to be able to build machine learning models.
5) You want to be ahead of the Curve
The data engineer and machine learning engineer roles are fairly new. While you’re learning, building your skills and becoming certified you are also the first to be part of this burgeoning field. You know that the first to be certified means the first to be hired and first to receive the top compensation package.
Thanks for interest in Data Wrangling in Pandas for Machine Learning Engineers
See you in the course!!
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: Is this Course for You?
Lecture 3: What is Pandas?
Lecture 4: What is Data Wrangling
Lecture 5: Summary
Lecture 6: Common Interview Questions – Section 1
Chapter 2: Pandas Dataframe Basics
Lecture 1: Download Raw Titanic Data Set
Lecture 2: Load a Data Set in Pandas
Lecture 3: Data Types
Lecture 4: Columns, Rows and Cells
Lecture 5: Using Loc
Lecture 6: iloc and ix
Lecture 7: Subsetting Rows and Columns
Lecture 8: Lab: Slicing Dataframes
Lecture 9: Grouped and Aggregated Calculations
Lecture 10: Grouped frequency counts
Lecture 11: Lab: Grouping
Lecture 12: Summary
Lecture 13: Common Interview Questions – Section 2
Chapter 3: Pandas data structures
Lecture 1: The Series Object
Lecture 2: Series Anatomy
Lecture 3: Lab: Working with the Series Object
Lecture 4: Attributes
Lecture 5: An Array Defined
Lecture 6: The Series and Numpy Array
Lecture 7: Lab: Descriptive Statistics For pandas Dataframe
Lecture 8: Boolean Subsetting with the Series
Lecture 9: Vectorized Operations
Lecture 10: Lab: Row Based Conditional Searches
Lecture 11: Replacing Values in Pandas
Lecture 12: Lab: Saving A Pandas Dataframe As A CSV
Lecture 13: Rename Column Header In Pandas
Lecture 14: Sorting Rows in a Pandas Dataframe
Lecture 15: Read Excel Files
Lecture 16: Regular Expression in Pandas
Lecture 17: Binning Data
Lecture 18: Normalize Data in Pandas
Lecture 19: Lab: Data Normalization
Lecture 20: Data Normalization Lab Line by Line
Lecture 21: Summary
Lecture 22: Common Interview Questions – Section 3
Chapter 4: Introduction to Plotting
Lecture 1: Install Seaborn Via Anaconda
Lecture 2: Matplotlib
Lecture 3: Lab: Matplotlib Basics
Lecture 4: Using Seaborn with a Pandas Dataframe
Lecture 5: Lab: Seaborn Basics
Lecture 6: Summary
Lecture 7: Common Interview Questions – Section 4
Chapter 5: Data Assembly
Lecture 1: File Concatenation
Lecture 2: Row Concatenation
Lecture 3: Lab: Concatenation
Lecture 4: Merging
Lecture 5: Right, Left and Outer Joins
Lecture 6: Lab: Merge Function
Lecture 7: Summary
Lecture 8: Common Interview Questions – Section 5
Chapter 6: Missing Data
Lecture 1: Evaluate Missing Data
Lecture 2: Finding the NaNs
Lecture 3: Dropping out Missing Values
Lecture 4: Dropping Specific Cells
Lecture 5: NaN Value Differences
Lecture 6: Lab: Missing Data
Lecture 7: Filling Using Index Values
Lecture 8: Interpolation of missing values
Lecture 9: Handling Duplicate Data
Lecture 10: Lab: Duplicate Data
Lecture 11: Mapping
Lecture 12: The Replace Function
Lecture 13: Using Functions to Create Columns
Lecture 14: Lab: Breaking Up Strings
Lecture 15: Summary
Lecture 16: Common Interview Questions – Section 6
Chapter 7: Time Series Data
Lecture 1: Time Series Basics
Lecture 2: Timestamp Objects
Lecture 3: Lab: Time Series
Lecture 4: Timedelta
Lecture 5: The DatetimeIndex
Lecture 6: Force Datetime Function with Coerce
Lecture 7: The Frequency Parameter
Lecture 8: Frequency Table
Lecture 9: The DateOffset
Lecture 10: Built-in Date Offset Classes
Lecture 11: Lab: DateOffset
Lecture 12: Anchored Offsets
Lecture 13: Period Object
Lecture 14: Summary
Instructors
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Mike West
Creator of LogikBot
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 5 votes
- 3 stars: 19 votes
- 4 stars: 43 votes
- 5 stars: 49 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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