Deep Learning Dictionary - Lightweight Crash Course

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Machine Learning - Deep Learning Dictionary

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Machine Learning - Deep Learning Dictionary

Machine learning (ML) is a subfield of AI that uses algorithms to analyze data, learn from that data, improve, and then make a determination or prediction about new data.

drawing

The key distinction of machine learning algorithms as opposed to traditional non-ML algorithms is that ML algorithms learn from the data.

With machine learning, rather than a developer manually writing code with an explicit set of instructions to accomplish a specific task (as with traditional programming), the machine is instead trained using data and algorithms that give it the ability to learn from the data and perform the task without explicitly being told how to do so.

With a traditional programming approach, we might write a program that would classify an article from a health magazine as either "diet" or "exercise" based on whether the number of counted "diet words" was greater than or less than the number of "exercise words."

These words would be chosen by the developer. When there is a higher number of diet words, then the article is classified as a diet article. When there is a higher number of exercise words, the article is classified as exercise.

# pseudocode
diet = [
    "diet", 
    "food", 
    "eat"
]

exercise = [
    "exercise", 
    "movement", 
    "weightlifting"
]

On the other hand, with machine learning, we supply an algorithm with a dataset containing articles from the health magazine, and each article has been labeled by us as either being "diet" or "exercise."

# pseudocode
articles = [
    {
        label: "diet",
        data: "Wholegrains are a great source of fiber..."
    },
    {
        label: "diet",
        data: "Processed meats, like hotdogs..."
    },
    {
        label: "exercise",
        data: "Once your heartrate reaches..."
    },
    {
        label: "exercise",
        data: "Squats activate the quads..."
    }
]

Through some training process, the algorithm will analyze the data and learn the features that classify what a diet article looks like versus a exercise article.

With what it has learned from the dataset, the algorithm can then classify new articles as diet or exercise, although it was never given explicit instructions for how to do this classification from the developer of the program.

Within the field of machine learning, there are many types of learning algorithms that work with all types of data to achieve all sorts of tasks. Some common ML algorithms include:

  • Regression
  • Decision Trees
  • Support Vector Machines (SVM)
  • Naive Bayes Classifiers
  • K-Nearest Neighbor
  • Artificial Neural Networks (belongs to subfield of deep learning)

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What is machine learning? πŸ‘‰ To gain early access to the full Deep Learning Dictionary course, register at: πŸ”— https://deeplizard.com/course/ddcpailzrd πŸ‘‰ For more in depth lessons, check out the Deep Learning Fundamentals course: πŸ”— https://deeplizard.com/course/dlcpailzrd πŸ•’πŸ¦Ž VIDEO SECTIONS πŸ¦ŽπŸ•’ 00:00 Welcome to DEEPLIZARD - Go to deeplizard.com for learning resources 00:10 Machine Learning 03:55 Collective Intelligence and the DEEPLIZARD HIVEMIND πŸ’₯🦎 DEEPLIZARD COMMUNITY RESOURCES 🦎πŸ’₯ πŸ‘‹ Hey, we're Chris and Mandy, the creators of deeplizard! πŸ‘€ CHECK OUT OUR VLOG: πŸ”— https://youtube.com/deeplizardvlog πŸ‘‰ Check out the website for more learning material: πŸ”— https://deeplizard.com πŸ’» ENROLL TO GET DOWNLOAD ACCESS TO CODE FILES πŸ”— https://deeplizard.com/resources 🧠 Support collective intelligence, join the deeplizard hivemind: πŸ”— https://deeplizard.com/hivemind 🧠 Use code DEEPLIZARD at checkout to receive 15% off your first Neurohacker order πŸ‘‰ Use your receipt from Neurohacker to get a discount on deeplizard courses πŸ”— https://neurohacker.com/shop?rfsn=6488344.d171c6 ❀️🦎 Special thanks to the following polymaths of the deeplizard hivemind: Tammy Mano Prime Ling Li πŸš€ Boost collective intelligence by sharing this video on social media! πŸ‘€ Follow deeplizard: Our vlog: https://youtube.com/deeplizardvlog Facebook: https://facebook.com/deeplizard Instagram: https://instagram.com/deeplizard Twitter: https://twitter.com/deeplizard Patreon: https://patreon.com/deeplizard YouTube: https://youtube.com/deeplizard πŸŽ“ Deep Learning with deeplizard: Deep Learning Dictionary - https://deeplizard.com/course/ddcpailzrd Deep Learning Fundamentals - https://deeplizard.com/course/dlcpailzrd Learn TensorFlow - https://deeplizard.com/course/tfcpailzrd Learn PyTorch - https://deeplizard.com/course/ptcpailzrd Natural Language Processing - https://deeplizard.com/course/txtcpailzrd Reinforcement Learning - https://deeplizard.com/course/rlcpailzrd Generative Adversarial Networks - https://deeplizard.com/course/gacpailzrd πŸŽ“ Other Courses: DL Fundamentals Classic - https://deeplizard.com/learn/video/gZmobeGL0Yg Deep Learning Deployment - https://deeplizard.com/learn/video/SI1hVGvbbZ4 Data Science - https://deeplizard.com/learn/video/d11chG7Z-xk Trading - https://deeplizard.com/learn/video/ZpfCK_uHL9Y πŸ›’ Check out products deeplizard recommends on Amazon: πŸ”— https://amazon.com/shop/deeplizard 🎡 deeplizard uses music by Kevin MacLeod πŸ”— https://youtube.com/channel/UCSZXFhRIx6b0dFX3xS8L1yQ ❀️ Please use the knowledge gained from deeplizard content for good, not evil.

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