Ensemble Methods: Boosting, Bagging, Boostrap, and Statistical MachineLearning for Data Science in Python
In recent years, we've seen a resurgence in AI, or artificial intelligence, and machinelearning.
Machinelearning has led to some amazing results, like being able to analyze medical images...
A-Z Guide to Implementing Classic MachineLearning Algorithms From Scratch and with Sci-Kit Learn
In recent years, we've seen a resurgence in AI, or artificial intelligence, and machinelearning.
Machinelearning has led to some amazing results, like being able to analyze medical images and...
Data Science, MachineLearning, and Data Analytics Techniques for Marketing, Digital Media, Online Advertising, and more
This course is all about A/B testing.
A/B testing is used everywhere. Marketing, retail, newsfeeds, online advertising, and more.
A/B testing is all about comparing things.
If...
Data science techniques for pattern recognition, data mining, k-means clustering, and hierarchical clustering, and KDE.
Cluster analysis is a staple of unsupervised machinelearning and data science.
It is very useful for data mining and big data because it automatically finds patterns in the...
HMMs for stock price analysis, language modeling, web analytics, biology, and PageRank.
The Hidden Markov Model or HMM is all about learning sequences.
A lot of the data that would be very useful for us to model is in sequences. Stock prices are sequences of prices. Language is a sequence of...
Autoencoders + Restricted Boltzmann Machines for Deep Neural Networks in Theano, + t-SNE and PCA
This course is the next logical step in my deep learning, data science, and machinelearning series. I’ve done a lot of courses about deep learning, and I just released a course about unsupervised...
A guide for writing your own neural network in Python and Numpy, and how to do it in Google's TensorFlow.
This course will get you started in building your FIRST artificial neural network using deep learning techniques. Following my previous course on logistic regression, we take this basic...
Data science: Learn linear regression from scratch and build your own working program in Python for data analysis.
This course teaches you about one popular technique used inmachinelearning, data science and statistics: linear regression. We cover the theory from the ground up: derivation of...
Data science techniques for professionals and students - learn the theory behind logistic regression and code in Python
This course is a lead-in to deep learning and neural networks - it covers a popular and fundamental technique used inmachinelearning, data science and statistics: logistic...
GRU, LSTM, + more modern deep learning, machinelearning, and data science for sequences
*** NOW IN TENSORFLOW 2 and PYTHON 3 ***
Learn about one of the most powerful Deep Learning architectures yet!
The Recurrent Neural Network (RNN) has been used to obtain state-of-the-art results in sequence...
Computer Vision and Data Science and MachineLearning combined! In Theano and TensorFlow
*** NOW IN TENSORFLOW 2 and PYTHON 3 ***
Learn about one of the most powerful Deep Learning architectures yet!
The Convolutional Neural Network (CNN) has been used to obtain state-of-the-art results in...
Take deep learning to the next level with SGD, Nesterov momentum, RMSprop, Theano, TensorFlow, and using the GPU on AWS.
This course continues where my first course, Deep Learningin Python, left off. You already know how to build an artificial neural network in Python, and you have a...
Complete guide on deriving and implementing word2vec, GLoVe, word embeddings, and sentiment analysis with recursive nets
In this course we are going to look at NLP (natural language processing) with deep learning.
Previously, you learned about some of the basics, like how many NLP problems are...
Здравствуйте, друзья!
Добро пожаловать в раздел "Машинное обучение: Обработка естественного языка на Python (версия 2).
Это обширный курс "4 в 1", включающий в себя:
Векторные модели и методы предварительной обработки текста
Вероятностные модели и марковские модели
Методы машинного обучения...
Advanced AI: Deep Reinforcement Learningin Python
Полное руководство по освоению искусственного интеллекта с помощью глубокого обучения и нейронных сетей.
Чему вы научитесь:
Создание различных агентов глубокого обучения (включая DQN и A3C)
Применяйте различные передовые алгоритмы обучения с...
MachineLearning and AI: Support Vector Machines in Python
Искусственный интеллект и наука о данных Алгоритмы классификации и регрессии на Python
Чему вы научитесь:
Применяйте SVM в практических приложениях: распознавание изображений, обнаружение спама, медицинская диагностика и регрессионный...
Please note: Only the VIP version of the course covers Face Swap / Face Swapping. Contact the instructor if you are unsure of what that means!
Unleash Your Creative Potential with DeepFakes Mastery
Unlock the captivating power of DeepFakes and embark on a groundbreaking journey where reality and...
A-Z guide to practical NLP: spam detection, sentiment analysis, article spinners, and latent semantic analysis.
In this course you will build MULTIPLE practical systems using natural language processing, or NLP - the branch of machinelearning and data science that deals with text and speech...
Язык: Английский
Полное руководство по получению и реализации word2vec, GloVe, вкраплений слов и анализа настроения с помощью рекурсивных сетей
Чему вы научитесь:
Понять и реализовать word2vec
Понять метод CBOW в word2vec
Понять метод пропусков в word2vec
Понять оптимизацию отрицательной...
Нейронные сети для компьютерного зрения, прогнозирования временных рядов, НЛП, GANs, Reinforcement Learning и многое другое!
Требования:
Уметь писать код на Python и Numpy
Для теоретической части (по выбору) - понимание производных и вероятности
Описание:
Вы когда-нибудь задумывались...