A series of Jupyter notebooks teaches machine learning and deep learning in Python with Scikit-Learn, Keras, and TensorFlow.
Open source
24 alternativesMachine Learning Roadmap
vsData Science Ipython Notebooks
Machine Learning Roadmap vs Data Science Ipython Notebooks
How do Machine Learning Roadmap and Data Science Ipython Notebooks compare? Here are the facts side by side: pricing, platforms, open-source status and what each one is for.
| Directory detail | Machine Learning Roadmap | Data Science Ipython Notebooks |
|---|---|---|
| What it is | This machine learning roadmap lays out a learning path that starts with mathematics and calculus fundamentals. | Data Science IPython Notebooks collects notebooks about data science, including TensorFlow deep learning. |
| Website | ||
| Type | Website | Open-source project |
| Topic | ||
| Pricing | Not confirmed | Not confirmed |
| Platforms | Web | Not recorded |
| Open source | Not stated | Not stated |
| Language | — | English |
| Alternatives |
Other options to consider
Sites similar to both Machine Learning Roadmap and Data Science Ipython Notebooks.
Virgilio organizes data science e-learning resources in a structured project overview.
Codecademy’s Machine Learning Specialist path covers Python, SQL, pandas, scikit-learn, Matplotlib, and TensorFlow.
Jupyter notebooks implement and derive machine learning algorithms from first principles using NumPy.
Open source
24 alternatives
Deep-ML provides hands-on exercises in machine learning and data science fundamentals.
This open book collects methods, tools, and instructions for training, fine-tuning, and running machine learning models.