Data science techniques for pattern recognition, data mining, k-means clustering, and hierarchical clustering, and KDE.
Clusteranalysis is a staple of unsupervisedmachinelearningand 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, andmachinelearning series. I’ve done a lot of courses about deep learning, and I just released a course about unsupervised...
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, andmachinelearning.
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...
Ensemble Methods: Boosting, Bagging, Boostrap, and Statistical MachineLearning for Data Science inPythonIn recent years, we've seen a resurgence in AI, or artificial intelligence, andmachinelearning.
Machinelearning has led to some amazing results, like being able to analyze medical images...
A guide for writing your own neural network inPythonand 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 inPython 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...
GRU, LSTM, + more modern deep learning, machinelearning, and data science for sequences
*** NOW IN TENSORFLOW 2 andPYTHON 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...
Data science techniques for professionals and students - learn the theory behind logistic regression and code inPython
This course is a lead-in to deep learningand neural networks - it covers a popular and fundamental technique used inmachinelearning, data science and statistics: logistic...
Computer Vision and Data Science andMachineLearning combined! In Theano and TensorFlow
*** NOW IN TENSORFLOW 2 andPYTHON 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 LearninginPython, left off. You already know how to build an artificial neural network inPython, 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...
MachineLearningand AI: Support Vector Machines inPython
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...
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 LearninginPython
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...
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 machinelearningand 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...
Dominate data analytics, data science, and big data
It is becoming ever more important that companies make data-driven decisions.
With big data and data science on the rise, we have more data than we know what to do with.
One of the basic languages of data analytics is SQL, which is used for...