| 1 |
|
Python Machine Learning
by
4.25 avg rating — 755 ratings
|
|
| 2 |
|
The Statistics and Calculus with Python Workshop: A comprehensive introduction to mathematics in Python for artificial intelligence applications
by
really liked it 4.00 avg rating — 5 ratings
|
|
| 3 |
|
Exploring GPT-3: An unofficial first look at the general-purpose language processing API from OpenAI
by
3.48 avg rating — 29 ratings
|
|
| 4 |
|
Hands-On Gradient Boosting with XGBoost and scikit-learn: Perform accessible machine learning and extreme gradient boosting with Python
by
4.06 avg rating — 35 ratings
|
|
| 5 |
|
Machine Learning Using TensorFlow Cookbook: Create powerful machine learning algorithms with TensorFlow
by
2.33 avg rating — 3 ratings
|
|
| 6 |
|
Practical Discrete Mathematics: Discover math principles that fuel algorithms for computer science and machine learning with Python
by
4.29 avg rating — 7 ratings
|
|
| 7 |
|
The TensorFlow Workshop: A hands-on guide to building deep learning models from scratch using real-world datasets
by
4.50 avg rating — 2 ratings
|
|
| 8 |
|
Algorithmic Short Selling with Python: Refine your algorithmic trading edge, consistently generate investment ideas, and build a robust long/short product
by
3.72 avg rating — 18 ratings
|
|
| 9 |
|
Machine Learning Engineering with Python: Manage the production life cycle of machine learning models using MLOps with practical examples
by
3.71 avg rating — 7 ratings
|
|
| 10 |
|
Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more
by
4.09 avg rating — 65 ratings
|
|
| 11 |
|
Machine Learning for Algorithmic Trading: Predictive Models to Extract Signals from Market and Alternative Data for Systemic Trading Strategies with Python
by
4.11 avg rating — 63 ratings
|
|
| 12 |
|
Applied Deep Learning and Computer Vision for Self-Driving Cars: Build autonomous vehicles using deep neural networks and behavior-cloning techniques
by
3.33 avg rating — 6 ratings
|
|
| 13 |
|
Modern Computer Vision with PyTorch: Explore deep learning concepts and implement over 50 real-world image applications
by
4.11 avg rating — 19 ratings
|
|
| 14 |
|
Interpretable Machine Learning with Python: Learn to build interpretable high-performance models with hands-on real-world examples
by
4.31 avg rating — 16 ratings
|
|
| 15 |
|
Graph Machine Learning: Take graph data to the next level by applying machine learning techniques and algorithms
by
3.71 avg rating — 7 ratings
|
|
| 16 |
|
Mastering Transformers: Build state-of-the-art models from scratch with advanced natural language processing techniques
by
4.06 avg rating — 17 ratings
|
|
| 17 |
|
The Machine Learning Solutions Architect Handbook: Create machine learning platforms to run solutions in an enterprise setting
by
4.06 avg rating — 16 ratings
|
|
| 18 |
|
Advanced Natural Language Processing with TensorFlow 2: Build effective real-world NLP applications using NER, RNNs, seq2seq models, Transformers, and more
by
4.20 avg rating — 5 ratings
|
|
| 19 |
|
Getting Started with Streamlit for Data Science: Create and deploy Streamlit web applications from scratch in Python
by
4.20 avg rating — 20 ratings
|
|
| 20 |
|
Machine Learning for Time-Series with Python: Forecast, predict, and detect anomalies with state-of-the-art machine learning methods
by
3.56 avg rating — 18 ratings
|
|
| 21 |
|
Learn Amazon SageMaker: A guide to building, training, and deploying machine learning models for developers and data scientists
by
4.07 avg rating — 15 ratings
|
|
| 22 |
|
Mastering Azure Machine Learning: Perform large scale end-to-end advanced machine learning on Cloud with Microsoft Azure
by
4.25 avg rating — 4 ratings
|
|
| 23 |
|
Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more
by
4.18 avg rating — 44 ratings
|
|
| 24 |
|
Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python
by
4.42 avg rating — 104 ratings
|
|
| 25 |
|
The Kaggle Book: Data analysis and machine learning for competitive data science
by
4.27 avg rating — 73 ratings
|
|
