Final Remarks

Here's a quick summary of the "Machine Learning Basics" module.

We'll cover the following

Summary
What’s next?

Congratulations! We successfully completed the “Machine Learning Basics” module. 🎉

Summary

Starting off with data pre-processing, we learned about data modeling and eventually applied our learning to practical problems using various machine learning frameworks. This module also introduced us to two deep learning libraries, Tensorflow and Keras.

What’s next?

Now that we are familiar with the basic concepts of machine learning, it’s time for us to focus on creating image recognition algorithms used in computer vision and self-driving cars.

Before We Begin

Are You Ready to Become a Machine Learning Engineer?

Data Manipulation with NumPy

Data Analysis with pandas

Data Preprocessing with scikit-learn

Data Modeling with scikit-learn

Clustering with scikit-learn

Gradient Boosting with XGBoost

Deep Learning with TensorFlow

Deep Learning with Keras

Conclusion

Final Remarks

Summary

What’s next?