Machine Learning 101
Python for Machine Learning
Take the first step to ML and AI
Enroll Now for Free Machine Learning 101
In this online meetup, we will discuss the main categories of Machine Learning and implement some algorithms using the Python programming language.
In this session, we will closely examine supervised machine learning algorithms using scikit-learn, a core Python library for machine learning. We will delve into coding problems such as linear regression and K-Nearest Neighbors (KNN).
Linear Regression and K-Nearest Neighbors (KNN) are pivotal machine learning algorithms with distinct applications. Linear regression forms the bedrock for comprehending and modeling relationships between variables, particularly for predictive modeling tasks like sales forecasting, stock price prediction, and health outcome analysis. Its transparency through interpretable coefficients allows for understanding how each input variable influences the prediction. Moreover, it acts as a baseline model for evaluating the efficacy of more complex machine learning models, providing a benchmark for model performance.
On the other hand, KNN stands out due to its non-parametric, instance-based nature, making it suitable for cases with complex or unknown data distributions. It serves a dual role in both classification and regression tasks, offering versatility across a spectrum of data types, including numerical and categorical attributes. KNN's ability to capture local patterns and relationships within the data, coupled with its adaptability for use in recommendation systems, anomaly detection, and pattern recognition, makes it an indispensable tool for various machine learning problems. In essence, linear regression and KNN contribute significantly to the machine learning landscape, each offering unique strengths and versatility for addressing diverse real-world challenges.
Instructors
Art Yudin
Testimonials
I loved Art! He’s super patient and answers all questions! I recommend this class for all python beginners!! I had no knowledge of python prior to this class
Always enjoy taking a class with Art. He is knowledgeable and on top of his game. His class is quick paced but easy to follow... is patient with questions
I took Introduction to Python and Web Scrapping with Art and the class was great!
Took Python for Data Science Immersive with Art. Great instructor! Boost my knowledge within very short time frame!
Art is very thorough, helpful and able to break down content in a way it is easily digestible by those in attendance.
Art is great. Very generous with time and knowledge and truly helpful. Great if you have no programming knowledge or if you're a more advanced student.
Art is super helpful and attentive to every question.
Art teaches Python in a very understandable way.
Art has a ton of experience in teaching the basics of python to people who have no previous coding experience. The class format is great - we start with lectures and go right into practice problems to use what we just learned. 100% would recommended!
Art does a great job meeting everyone at their level and making sure that everyone feels challenged.
Questions? Check here
While a strong background in mathematics can be beneficial when delving deeper into machine learning, it is not an absolute requirement to get started. The level of mathematical knowledge you need depends on your goals within the field of machine learning.
You don't need to install anything before attending this free Python class. We'll be utilizing the Google online solution, Google Colab https://colab.research.google.com/, which only requires a Google login and password. With Colab, you can leverage the capabilities of well-known Python libraries to analyze and visualize data.
Python Intensive serves as a fundamental stepping stone to Python Data Science. Within Python Intensive, we establish a strong foundation by imparting essential Python skills, which you can subsequently leverage in Python for Data Science to collect, manipulate, and analyze data.
While individuals with prior Python expertise can directly enroll in Python Data Science, newcomers to Python programming are strongly encouraged to begin with Python Intensive for a smoother learning experience.
Python, a high-level and versatile programming language, offers a simpler syntax compared to languages like C#, C++, or Java. Consequently, learning Python syntax is a faster process, with many individuals achieving proficiency in as little as six months. Your mastery of Python largely hinges on your daily coding practice; Dedicating 5-7 hours each day could provide you with a working knowledge of Python in just two months.
While a strong background in mathematics can be beneficial when delving deeper into machine learning, it is not an absolute requirement to get started. The level of mathematical knowledge you need depends on your goals within the field of machine learning.
You don't need to install anything before attending this free Python class. We'll be utilizing the Google online solution, Google Colab https://colab.research.google.com/, which only requires a Google login and password. With Colab, you can leverage the capabilities of well-known Python libraries to analyze and visualize data.
Python Intensive serves as a fundamental stepping stone to Python Data Science. Within Python Intensive, we establish a strong foundation by imparting essential Python skills, which you can subsequently leverage in Python for Data Science to collect, manipulate, and analyze data.
While individuals with prior Python expertise can directly enroll in Python Data Science, newcomers to Python programming are strongly encouraged to begin with Python Intensive for a smoother learning experience.
Python, a high-level and versatile programming language, offers a simpler syntax compared to languages like C#, C++, or Java. Consequently, learning Python syntax is a faster process, with many individuals achieving proficiency in as little as six months. Your mastery of Python largely hinges on your daily coding practice; Dedicating 5-7 hours each day could provide you with a working knowledge of Python in just two months.
Python Intensive serves as a fundamental stepping stone to Python Data Science. Within Python Intensive, we establish a strong foundation by imparting essential Python skills, which you can subsequently leverage in Python for Data Science to collect, manipulate, and analyze data. While individuals with prior Python expertise can directly enroll in Python Data Science, newcomers to Python programming are strongly encouraged to begin with Python Intensive for a smoother learning experience.
Python, a high-level and versatile programming language, offers a simpler syntax compared to languages like C#, C++, or Java. Consequently, learning Python syntax is a faster process, with many individuals achieving proficiency in as little as six months. Your mastery of Python largely hinges on your daily coding practice; Dedicating 5-7 hours each day could provide you with a working knowledge of Python in just two months.