Придбаний Машинное обучение с Python + Big Data (15 курсов Udemy) [EN]

[Gadzhi]

Машинное обучение с Python + Big Data (15 курсов Udemy) [EN]


Комплект курсов (course bundle) Udemy (15 шт.). Основной акцент уделяется машинному обучению на Python, но так же есть введение в анализ Big Data.

Все 15 курсов почти полностью охватывают такие основные темы машинного обучения, как обучение с учителем (supervised learning), обучение без учителя (unsupervised learning), а так же глубинное обучение (deep learning) и др.

Материал хорошо структурирован и имеет отличные отзывы. Каждый курс по 2-5 часов, исходные коды на Python прилагаются.

Каждый курс берется по минималке 10 долл. за 1 курс, скидка по купону "BARRIER202" более 90% действует до 1 марта.

Об авторе
I am a data scientist, big data engineer, and full stack software engineer.

For my masters thesis I worked on brain-computer interfaces using machine learning. These assist non-verbal and non-mobile persons communicate with their family and caregivers.

I have worked in online advertising and digital media as both a data scientist and big data engineer, and built various high-throughput web services around said data. I've created new big data pipelines using Hadoop/Pig/MapReduce. I've created machine learning models to predict click-through rate, news feed recommender systems using linear regression, Bayesian Bandits, and collaborative filtering and validated the results using A/B testing.

I have taught undergraduate and graduate students in data science, statistics, machine learning, algorithms, calculus, computer graphics, and physics for students attending universities such as Columbia University, NYU, Humber College, and The New School.

Multiple businesses have benefitted from my web programming expertise. I do all the backend (server), frontend (HTML/JS/CSS), and operations/deployment work. Some of the technologies I've used are: Python, Ruby/Rails, PHP, Bootstrap, jQuery (Javascript), Backbone, and Angular. For storage/databases I've used MySQL, Postgres, Redis, MongoDB, and more.

Отзывы о курсах:
eduard1 сказал(а):

Материал стОящий - отзывы отличные, содержание насыщенное, каждый курс по 3-5 часов, чётко структурированные уроки.
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empiric сказал(а):

Отзывы хорошие, прилагается код на Python ко всем курсам на github.
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СПИСОК КУРСОВ (в хронологическом порядке их появления на Udemy)
Скрытое содержимое.

Список курсов в хронологическом порядке их появления на Udemy:

1. Deep Learning Prerequisites: Linear Regression in Python [556954]
Data science: Learn linear regression from scratch and build your own working program in Python for data analysis.


2. Deep Learning Prerequisites: Logistic Regression in Python [659368]
Data science techniques for professionals and students - learn the theory behind logistic regression and code in Python


3. Data Science: Deep Learning in Python [713104]
A guide for writing your own neural network in Python and Numpy, and how to do it in Google's TensorFlow.


4. Easy Natural Language Processing (NLP) in Python [753140]
A-Z guide to practical NLP: spam detection, sentiment analysis, article spinners, and latent semantic analysis.


5. Data Science: Practical Deep Learning in Theano + TensorFlow [772462]
Take deep learning to the next level with SGD, Nesterov momentum, RMSprop, Theano, TensorFlow, and using the GPU on AWS.


6. Data Analytics: SQL for newbs, beginners and marketers [794306]
Dominate data analytics, data science, and big data


7. Deep Learning: Convolutional Neural Networks in Python [807904]
Computer Vision and Data Science and Machine Learning combined! In Theano and TensorFlow


8. Cluster Analysis and Unsupervised Machine Learning in Python [825684]
Data science techniques for pattern recognition, data mining, k-means clustering, and hierarchical clustering, and KDE.


9. Unsupervised Deep Learning in Python [846480]
Autoencoders + Restricted Boltzmann Machines for Deep Neural Networks in Theano, + t-SNE and PCA


10. Unsupervised Machine Learning Hidden Markov Models in Python [872834]
HMMs for stock price analysis, language modeling, web analytics, biology, and PageRank.


11. Deep Learning: Recurrent Neural Networks in Python [887814]
GRU, LSTM, + more modern deep learning, machine learning, and data science for sequences


12. Natural Language Processing with Deep Learning in Python [918390]
Complete guide on deriving and implementing word2vec, GLoVe, word embeddings, and sentiment analysis with recursive nets


13. Data Science: Supervised Machine Learning in Python [944014]
A-Z Guide to Implementing Classic Machine Learning Algorithms From Scratch and with Sci-Kit Learn


14. Deep Learning Prerequisites: The Numpy Stack in Python [980086] (бесплатный курс от автора)
The Numpy, Scipy, Pandas, and Matplotlib stack: prep for deep learning, machine learning, and artificial intelligence


15. Bayesian Machine Learning in Python: A/B Testing [1011712]
Data Science, Machine Learning, and Data Analytics Techniques for Marketing, Digital Media, Online Advertising, and more


16. Ensemble Machine Learning in Python: Random Forest, AdaBoost [1041564]
Ensemble Methods: Boosting, Bagging, Boostrap, and Statistical Machine Learning for Data Science in Python


17. Artificial Intelligence - Reinforcement Learning in Python [1080408] (бесплатный курс бонус от орга)
Complete guide to artificial intelligence and machine learning, prep for deep reinforcement learning
https://www.udemy.com/artificial-intelligence-reinforcement-learning-in-python/