HomeCoursesMachine Learning with NumPy, pandas, scikit-learn, and More

Intermediate

15h

Machine Learning with NumPy, pandas, scikit-learn, and More

Delve into practical machine learning with NumPy, pandas, scikit-learn, and more. Gain insights into data analysis, feature engineering, and deep learning using industry-standard frameworks. Basic Python required.

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Overview

Content

Reviews

If you're a software engineer looking to add machine learning to your skillset, this is the place to start. This course will teach you to write useful code and create impactful machine learning applications immediately. From the start, you'll be given all the tools that you need to create industry-level machine learning projects. Rather than reading through dense theory, you’ll learn practical skills and gain actionable insights. Topics covered include data analysis/visualization, feature engineering, supervised learning, unsupervised learning, and deep learning. All of these topics are taught using industry-standard frameworks: NumPy, pandas, scikit-learn, XGBoost, TensorFlow, and Keras. Basic knowledge of Python is a prerequisite to this course. This course was created by AdaptiLab, a company specializing in evaluating, sourcing, and upskilling enterprise machine learning talent. It is built in collaboration with industry machine learning experts from Google, Microsoft, Amazon, and Apple.

If you're a software engineer looking to add machine learning to your skillset, this is the place to start. This course will t...Show More

Content

87 Lessons8 Quizzes115 Challenges

What you'll learn from this course

1 Lessons

Get familiar with machine learning processes, types, and model building essentials.

Overview

Data Manipulation with NumPy

11 Lessons

Grasp the fundamentals of data manipulation with NumPy arrays, arithmetic operations, and statistical analysis.

Data Analysis with pandas

14 Lessons

Master the steps to utilize pandas for MLB data analysis, including processing, manipulation, and visualization.

Data Preprocessing with scikit-learn

9 Lessons

Grasp the fundamentals of scikit-learn's data preprocessing techniques for scaling, normalizing, imputing, and dimensional reduction.

PCA

Data Modeling with scikit-learn

13 Lessons

Dig into scikit-learn's data modeling techniques, including linear regression, classification, and hyperparameter tuning.

Applying CV to Decision Trees

Evaluating Models

Exhaustive Tuning

Quiz

Clustering with scikit-learn

10 Lessons

Follow the process of clustering algorithms, evaluating their performance, and feature clustering in scikit-learn.

Hierarchical Clustering

Mean Shift Clustering

Gradient Boosting with XGBoost

10 Lessons

Build on XGBoost for efficient, high-performance gradient-boosted decision trees in data science.

Hyperparameter Tuning

Model Persistence

Quiz

Deep Learning with TensorFlow

12 Lessons

Learn how to use TensorFlow for neural networks, from MLPs to multiclass classifications.

Deep Learning with Keras

7 Lessons

Get started with creating, configuring, and evaluating neural network models using Keras.

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

Adaptilab

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Developed by MAANG Engineers

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Hands-on Learning Powered by AI

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Personalized Interview Prep

Skip the LeetCode grind with a custom roadmap that adapts to your goals. Hands-on practice for Coding Interviews, System Design, and more.

Mock Interviews

Test your skills in a simulated interview setting. Receive personalized feedback based on your performance. Available for Coding Interviews, System Design, and more.

AI Prompt

Build prompt engineering skills. Practice implementing AI-informed solutions.

Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

Explain with AI

Select any text within any Educative course, and get an instant explanation — without ever leaving your browser.

AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!

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