Machine Learning with Python

via freeCodeCamp

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Provider

freeCodeCamp
Pricing

Free Certificate
Languages

English
Certificate

Certificate Available
Duration & workload

300 hours
Sessions

On-Demand

Found in

Overview

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Machine learning has many practical applications that you can use in your projects or on the job.

In the Machine Learning with Python Certification, you'll use the TensorFlow framework to build several neural networks and explore more advanced techniques like natural language processing and reinforcement learning.

You'll also dive into neural networks, and learn the principles behind how deep, recurrent, and convolutional neural networks work.

Major Topics:

TensorFlow
How Neural Networks Work
Machine Learning with Python Projects

Syllabus

Introduction: Machine Learning Fundamentals
Introduction to TensorFlow
Core Learning Algorithms
Core Learning Algorithms: Working with Data
Core Learning Algorithms: Training and Testing Data
Core Learning Algorithms: The Training Process
Core Learning Algorithms: Classification
Core Learning Algorithms: Building the Model
Core Learning Algorithms: Clustering
Core Learning Algorithms: Hidden Markov Models
Core Learning Algorithms: Using Probabilities to make Predictions
Neural Networks with TensorFlow
Neural Networks: Activation Functions
Neural Networks: Optimizers
Neural Networks: Creating a Model
Convolutional Neural Networks
Convolutional Neural Networks: The Convolutional Layer
Creating a Convolutional Neural Network
Convolutional Neural Networks: Evaluating the Model
Convolutional Neural Networks: Picking a Pretrained Model
Natural Language Processing With RNNs
Natural Language Processing With RNNs: Part 2
Natural Language Processing With RNNs: Recurring Neural Networks
Natural Language Processing With RNNs: Sentiment Analysis
Natural Language Processing With RNNs: Making Predictions
Natural Language Processing With RNNs: Create a Play Generator
Natural Language Processing With RNNs: Building the Model
Natural Language Processing With RNNs: Training the Model
Reinforcement Learning With Q-Learning
Reinforcement Learning With Q-Learning: Part 2
Reinforcement Learning With Q-Learning: Example
Conclusion
How Deep Neural Networks Work
Recurrent Neural Networks RNN and Long Short Term Memory LSTM
Deep Learning Demystified
How Convolutional Neural Networks work
Rock Paper Scissors
Cat and Dog Image Classifier
Book Recommendation Engine using KNN
Linear Regression Health Costs Calculator
Neural Network SMS Text Classifier

Taught by

freeCodeCamp Team

Reviews

4.6 rating, based on 12 Class Central reviews

Start your review of Machine Learning with Python

Alok Kumar @alok2506

The freeCodeCamp Machine Learning course is a great introduction to the field of machine learning. The course covers a wide range of topics, including supervised and unsupervised learning models, and provides practical examples of how to program dif…

The freeCodeCamp Machine Learning course is a great introduction to the field of machine learning. The course covers a wide range of topics, including supervised and unsupervised learning models, and provides practical examples of how to program different machine learning models on Google Collab.

The course is developed by Kylie Ying, a Physicist, Engineer, and an excellent teacher who has worked at places like MIT, CERN, and freeCodeCamp. The course is well-structured and covers the logic and math behind the different machine learning models in a clear and concise manner.

One of the best things about the course is that it is completely free and available on the freeCodeCamp YouTube channel. The course is also supported by a grant from Google, which allows it to be accessible to a wide range of learners.

The course is structured in a way that gradually increases in complexity, and it touches on some handy techniques for debugging models. The course is also built around the popular machine learning workflow, which covers problem evaluation, data exploration, data preprocessing, model training/testing/deployment, and more.

Overall, I highly recommend the freeCodeCamp Machine Learning course to anyone who is interested in learning about machine learning. The course is well-structured, covers a wide range of topics, and provides practical examples of how to program different machine learning models. The fact that it is completely free and available on the freeCodeCamp YouTube channel makes it even more accessible to a wide range of learners.
SINDAVALAM BASAVA

I recently completed the Machine Learning course on FreeCodeCamp, and I must say, it was an incredibly rewarding experience. The course does a great job of breaking down complex machine learning concepts into digestible lessons, making it ideal fo…

I recently completed the Machine Learning course on FreeCodeCamp, and I must say, it was an incredibly rewarding experience. The course does a great job of breaking down complex machine learning concepts into digestible lessons, making it ideal for beginners as well as those looking to reinforce their understanding of the fundamentals.

**What I Liked:**

1. **Practical Approach:** The course takes a hands-on approach, which I really appreciated. There are plenty of coding challenges and projects that help you apply the concepts in real-world scenarios. This makes the learning more engaging and helps solidify your understanding.

2. **Python Focus:** The course is built around Python, a popular language for machine learning. You get to work with libraries like NumPy, pandas, and TensorFlow, which are essential tools in the ML toolkit.

3. **Clear Explanations:** The course creators have done a fantastic job in explaining difficult topics like supervised learning, decision trees, and neural networks in a way that's easy to follow. Even if you're new to machine learning, the content is presented clearly, and you can go at your own pace.

4. **Community Support:** FreeCodeCamp has an active community where you can ask questions, get help, or find study partners. This was really helpful when I encountered roadblocks during the projects.

**Areas for Improvement:**

1. **Advanced Topics:** While the course covers a wide range of topics, it focuses more on the basics. I would love to see more in-depth material on advanced topics like deep learning, reinforcement learning, or model optimization.

2. **More Projects:** Although the course includes several projects, a few more complex real-world examples could be added to give learners a deeper understanding of how to deploy ML models in production.
Mohsin Ilyas

The Machine Learning course was exceptional, offering a comprehensive blend of theory and practical applications. The instructors were knowledgeable and engaging, providing clear explanations and real-world examples. The course covered essential topics like supervised and unsupervised learning, deep learning, and reinforcement learning. The hands-on projects were particularly beneficial, allowing me to apply concepts immediately. Overall, this course significantly deepened my understanding of machine learning and equipped me with valuable skills for my career. Highly recommended for anyone looking to delve into the world of machine learning.
YARRAGOLLA VENKATA SAI

"This course offers a solid introduction to Machine Learning using Python. The explanations are clear, and the practical examples are really helpful. I found the course content to be engaging and well-structured, making it suitable for beginners. Overall, a great learning experience!"
Hari Krishnan S

classes are very easy to understand and cope up, detailed and slow pace. really loved learning. Got a great understanding on Machine Learning using Python,
Alberto Seabra Monteiro Neto

excelente curso que aborda com detalhes assuntos como machine learning e rede neurais.
Aborda com exemplos tipos de IA , como por exemplo LRN.
Muhammad Aqeel Sarwar

This course was really informative. Material provided and tutorial demonstration was excellent. It helped me gain valuable skills for my professional career.
Riyad Ahmadov

This machine learning course exceeded expectations with its well-structured curriculum, knowledgeable instructors, and hands-on projects. From fundamentals to advanced topics, the content was presented clearly, allowing a smooth learning curve. The instructors were actively engaged, fostering a sense of community. Practical projects, progressively challenging, reinforced theoretical concepts effectively. The course platform's user-friendly interface and flexibility in pacing enhanced the overall experience. Covering a range of algorithms and emphasizing practical skills, it provided valuable insights for real-world applications. Highly recommended for those seeking a comprehensive and engaging introduction to machine learning.
Hafedh Hedhly

This is best introductory programming course in python. Mentors are planting every concept in our head in very fluent ways. You must take take this course as a begineer python programmer like me.
Sadhwika Peri

Had a wonderfull experience and great use of knowledge. had a great time with you guys Thank you!! for wonderfull opportunity .
Pradnya Vitthal Todarmal

Best Course It is the Best Course for Machine Learning!

Sir has been like always has such important & difficult concepts of ML with such ease and great examples, Just amazing!
Rohit Pandey

This program is very excellent for any beginner and also a professional working and also Envolve advance course