What Should You Know about Data, ML, AI, and DeepLearning?
Understanding Basics knowledge for beginners
So, What do you think? A huge amount of data from day today. What will do with this data?
Discuss the stored data. Last decade, we still use a floppy disk or CD to store data. Manual paper records, save files, floppy, and disk. But, now, We can store all the data on the cloud. We can store and access it from anywhere and anytime. The exponential growth of data is so huge, it might Terrabyte, or petabytes.
You can make predictions based on data analysis, you can calculate probabilities with a specific result, and so on.
Let’s Imagine! How many people in the world today connect with others through social media. The YouTube views are 38,745,040, Twitter has 4.182,272 tweets, Instagram photos are 449,379, and the latest update is February 15, 2020. Imagine what would happen if you were on the internet. The frequency of audience watching Youtube videos is 24 million times, Google Search 26 million times, Facebook posted 18 million times, and so on. (Data real-time social media)
Big Data
With many ongoing waves of digital transformation, Big Data is important today. So what is Big Data? Big Data is a collection the huge data, complex, and growing exponentially, the speed when created and collect from multiple sources and multiple formats with the variety or scope data encompass unstructured, semi-structured, and structured results to capture, curate, manage, and process data within a tolerable in elapsed time.
Artificial Intelligence (AI)
AI changes the way we experience the world and increases attention in recent years. Innovation, The collection of Big Data, and the cause to grow the Internet of things (IoT) may have significant effects closer on our life.
Machine Learning (ML)
Machine Learning is a sub-area application of artificial intelligence (AI) that can access data and train independently to recognize patterns based on existing algorithms that find solutions to the problem. The machine can learn based on historical data then with the model to predict what happens in the future. A machine can learn and act like a human.
The Types of Machine Learning :
Supervised Learning
Unsupervised Learning
Reinforcement Learning
When I was a shortlisted candidate to be a freelance writer, I got a task to summarize a paper Big Self-Supervised Models are Strong Semi-Supervised Learners.
Semi-Supervised Learning (Semi-Supervised) is an alternative approach for computer vision because unlabelled data for a large amount of data can work well
DeepLearning
Deep learning is a subset of machine learning Cliches: it based on learning from large amounts of data and improving on its own by examining computer algorithms with artificial neural networks gives machines an enhanced ability to find and amplify, even the smallest patterns, algorithms inspired by the human brain filters information. This technique’s name is a deep neural network. Deep because the neural networks have various (deep) layers that enable learning through data and deliver an ultimate result in the prediction’s form.
My Learning Course :
Machine Learning For Business Professional, Google Cloud Training
