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📚 Become a professional data scientist with these 17 resources!
1️⃣ Python libraries for machine learning
◀️ Introducing the best Python tools and packages for building ML models.
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2️⃣ Deep Learning Interactive Book
◀️ Learn deep learning concepts by combining text, math, code, and images.
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3️⃣ Anthology of Data Science Learning Resources
◀️ The best courses, books, and tools for learning data science.
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4️⃣ Implementing algorithms from scratch
◀️ Coding popular ML algorithms from scratch
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5️⃣ Machine Learning Interview Guide
◀️ Fully prepared for job interviews
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6️⃣ Real-world machine learning projects
◀️ Learning how to build and deploy models.
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7️⃣ Designing machine learning systems
◀️ How to design a scalable and stable ML system.
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8️⃣ Machine Learning Mathematics
◀️ Basic mathematical concepts necessary to understand machine learning.
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9️⃣ Introduction to Statistical Learning
◀️ Learn algorithms with practical examples.
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1️⃣ Machine learning with a probabilistic approach
◀️ Better understanding modeling and uncertainty with a statistical perspective.
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1️⃣ UBC Machine Learning
◀️ Deep understanding of machine learning concepts with conceptual teaching from one of the leading professors in the field of ML,
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1️⃣ Deep Learning with Andrew Ng
◀️ A strong start in the world of neural networks, CNNs and RNNs.
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1️⃣ Linear Algebra with 3Blue1Brown
◀️ Intuitive and visual teaching of linear algebra concepts.
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🔴 Machine Learning Course
◀️ A combination of theory and practical training to strengthen ML skills.
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1️⃣ Mathematical Optimization with Python
◀️ You will learn the basic concepts of optimization with Python code.
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1️⃣ Explainable models in machine learning
◀️ Making complex models understandable.
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⚫️ Data Analysis with Python
◀️ Data analysis skills using Pandas and NumPy libraries.
✅ @Deeplearning_ai
BY Artificial Intelligence && Deep Learning
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