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Deep learning is part of a broader family of machine learning methods based on artificial neural networks. Machine learning is the study of algorithms and mathematical models that computer systems use to progressively improve their performance on a specific task. Machine learning algorithms build a mathematical model of sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task.The types of machine learning algorithms differ in their approach, the type of data they input and output, and the type of task or problem that they are intended to solve.Supervised learning algorithms build a mathematical model of a set of data that contains both the inputs and the desired outputs.Unsupervised learning algorithms take a set of data that contains only inputs, and find structure in the data, like grouping or clustering of data points. The algorithms therefore learn from test data that has not been labeled, classified or categorized.
Ninety percent of all the world’s data has been created in the last two years. Business around the world generate approximately 450 billion transactions a day. The amount of data collected by all organizations is approximately 2.5 exabytes a day. That number doubles every month.That means,there is always exponential need for Machine learning engineers to build, implement, and maintain machine learning systems,algorithms in technology products with focus on machine learning system reliability, performance, and scalability.
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Do check out earlier compilation on Data Science,Machine Learning and Artificial Intelligence courses.
Quick Snapshot
Accelerate your deep learning with PyTorch covering all the fundamentals of deep learning with a python-first framework.
Ratings : 4.4 (1,013 ratings)
Learn to apply machine learning to your problems. Follow a complete pipeline including pre-processing and training.
Ratings : 4.4 (246 ratings)
Word2Vec, Glove, FastText, Universal Sentence Encoder, GRU, LSTM, Conv-1D, Seq2Seq, Machine Translation and much more!
Ratings : 4.2 (24 ratings)
Learn to create Deep Learning Algorithms in Python from two Machine Learning & Data Science experts. Templates included.
Ratings : 4.5 (21,089 ratings)
Data science: Learn linear regression from scratch and build your own working program in Python for data analysis.
Ratings : 4.6 (3,058 ratings)
Data science techniques for professionals and students – learn the theory behind logistic regression and code in Python
Ratings :4.6 (2,207 ratings)
Build with modern libraries like Tensorflow, Theano, Keras, PyTorch, CNTK, MXNet. Train faster with GPU on AWS.
Ratings : 4.6 (1,629 ratings)
Complete guide on deriving and implementing word2vec, GloVe, word embeddings, and sentiment analysis with recursive nets.
Ratings : 4.6 (3,109 ratings)
The most in-depth course on recommendation systems with deep learning, machine learning, data science, and AI techniques
Ratings : 4.7 (468 ratings)
Become a Wizard of all the latest Computer Vision tools that exist out there. Detect anything and create powerful apps.
Ratings : 4.4 (2,981 ratings)
Apprenez crer des algorithmes de Deep Learning en Python par des experts en Machine Learning & Data science.
Ratings : 4.4 (1,147 ratings)
Understand and build Deep Learning models for images, text and more using Python and Keras
Ratings : 4.3 (1,868 ratings)
Deep Learning & Artificial Intelligence in Python: Bitcoin-Preise voraussagen, AI entwickeln – in Keras & Tensorflow
Ratings : 4.6 (502 ratings)
Learn how to use Google’s Deep Learning Framework – TensorFlow with Python! Solve problems with cutting edge techniques!
Ratings : 4.5 (10,659 ratings)
Learn the latest techniques in computer vision with Python, OpenCV, and Deep Learning!
Ratings : 4.5 (1,032 ratings)
Complete hands-on machine learning tutorial with data science, Tensorflow, artificial intelligence, and neural networks
Ratings : 4.5 (14,328 ratings)
Learn OpenCV4, Dlib, Keras, TensorFlow & Caffe while completing over 21 projects such as classifiers, detectors & more!
Ratings : 4.2 (2,487 ratings)
Learn to use Deep Learning, Computer Vision and Machine Learning techniques to Build an Autonomous Car with Python
Ratings : 4.6 (1,044 ratings)
Schritt fr Schritt entwickelst du dein eigenes neuronales Netz bis hin zur Bilderkennung. Komplett am Beispiel!
Ratings : 4.5 (381 ratings)
Beherrsche das Deep Learning fr eigene Neuronale Netzwerke. Nutze Python, TensorFlow und Keras um Probleme zu lsen.
Ratings : 4.5 (635 ratings)
Build Highly Sophisticated Deep Learning and Computer Vision Applications with PyTorch
Ratings : 4.6 (250 ratings)
Apprendi i segreti del Deep Learning e impara a creare le tue Reti Neurali Artificiali con Python, Keras e Tensorflow.
Ratings : 4.5 (72 ratings)
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