Merge branch 'master' into master

ML-DL Projects 2022

@@ -1,6 +1,7 @@
 Heart_Disease_Preditor
 Boston/California/Banglore_House_Price_Prectictor
 Car_Price/Sales_Predictor
+Cat Image Classifier
 CreditCard_Fraud/Scam_Predictor
 Customer_Segmentation
 Diabetes_Predictor

README.md

@@ -1083,6 +1083,7 @@ be
 * [BigARTM](https://github.com/bigartm/bigartm) - topic modelling platform.
 * [NALP](https://github.com/gugarosa/nalp) - A Natural Adversarial Language Processing framework built over Tensorflow.
 * [DL Translate](https://github.com/xhlulu/dl-translate) - A deep learning-based translation library between 50 languages, built with `transformers`.
+* [Haystack](https://github.com/deepset-ai/haystack) - A framework for building industrial-strength applications with Transformer models and LLMs.
 
 <a name="python-general-purpose-machine-learning"></a>
 #### General-Purpose Machine Learning
@@ -1244,6 +1245,7 @@ be
 * [cleanlab](https://github.com/cleanlab/cleanlab): The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
 * [AutoGluon](https://github.com/awslabs/autogluon): AutoML for Image, Text, Tabular, Time-Series, and MultiModal Data.
 * [PyBroker](https://github.com/edtechre/pybroker) - Algorithmic Trading with Machine Learning.
+* [Frouros](https://github.com/IFCA/frouros): Frouros is an open source Python library for drift detection in machine learning systems.
 
 
 <a name="python-data-analysis--data-visualization"></a>
@@ -1768,6 +1770,8 @@ be
 * [Distributed Machine Learning Patterns](https://github.com/terrytangyuan/distributed-ml-patterns)  - This book teaches you how to take machine learning models from your personal laptop to large distributed clusters. You’ll explore key concepts and patterns behind successful distributed machine learning systems, and learn technologies like TensorFlow, Kubernetes, Kubeflow, and Argo Workflows directly from a key maintainer and contributor, with real-world scenarios and hands-on projects.
 * [Grokking Machine Learning](https://www.manning.com/books/grokking-machine-learning) - Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math.
 * [Machine Learning Bookcamp](https://www.manning.com/books/machine-learning-bookcamp) - Learn the essentials of machine learning by completing a carefully designed set of real-world projects.
+* [Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow](https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1098125975) - Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.
+
 
 <a name="credits"></a>
 * [Netron](https://netron.app/) - An opensource viewer for neural network, deep learning and machine learning models

blogs.md

@@ -20,6 +20,7 @@ Podcasts
 * [TWIMLAI](https://twimlai.com/shows/)
 * [Machine Learning Guide](http://ocdevel.com/podcasts/machine-learning)
 * [DataTalks.Club](https://anchor.fm/datatalksclub)
+* [Super Data Science Podcast with Jon Krohn](https://www.youtube.com/@SuperDataScienceWithJonKrohn)
 
 Newsletters
 -----------

books.md

@@ -101,6 +101,8 @@ The following is a list of free and/or open source books on machine learning, st
 * [Natural Language Processing in Action, Second Edition](https://www.manning.com/books/natural-language-processing-in-action-second-edition) Early access book
 * [Getting Started with Natural Language Processing in Action](https://www.manning.com/books/getting-started-with-natural-language-processing) Early access book
 * [Transfer Learnin for Natural Language Processing](https://www.manning.com/books/transfer-learning-for-natural-language-processing) by Paul Azunre
+* [Practical Gradient Boosting](https://www.amazon.com/dp/B0BL1HRD6Z) by Guillaume Saupin
+
 
 ## Information Retrieval
 

courses.md

@@ -62,3 +62,4 @@ The following is a list of free or paid online courses on machine learning, stat
 * [DATA SCIENCE 360 TRAINING COURSE](https://brainalyst.in/data-science-360-training-course/)
 * [BIG DATA & CLOUD COMPUTING COURSE](https://brainalyst.in/big-data-cloud-computing-courses/)
 * [FULL STACK DATA SCIENCE PROGRAM](https://brainalyst.in/full-stack-data-science-course-program/)
+* [Mathematics for Machine Learning Specialization (Imperial College London via Coursera)](https://www.coursera.org/specializations/mathematics-machine-learning?action=enroll) - $ but financial aid available