Smitha Kolan is a Machine Learning Engineer, RU-vidr, and an Educator. She is a highly sought after expert in Machine Learning & AI and she is on a mission to help you understand these technologies.
This is awesome and amazing! Smitha is very clear, and explains things well. Finally someone that can teach a boring subject with enthusiasm! Keep the videos coming!
Thanks for series! Loving it. One way to use the kaggke dataset is to use the notebook that comes with kaggle. This will eliminate the need to download the datasets and connect to google-colabs.
I got some value error with this method. The updated method is def salary_model(y_new): # Create the training data xs = np.array([0, 1, 2, 3, 4, 5, 6], dtype=float) ys = np.array([0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1], dtype=float) # Define the model model = keras.Sequential([keras.layers.Dense(units=1, input_shape=[1])]) # Compile the model model.compile(optimizer='sgd', loss='mean_squared_error') # Train the model model.fit(xs, ys, epochs=50) # Ensure input for prediction is a 2D array y_new = np.array([[y_new]]) # Convert to a 2D array # Predict for the reshaped input return model.predict(y_new)[0][0]
He'll ma'am I'm Tabish ,I am pursuing diploma in chemical engineering from Delhi skill and entrepreneurship University in 2025. I want to learn Machine learning mastery ( Tutorial) . I saw your RU-vid channel, I hope I understand, please help me a little more.🙂
It's a BS regarding the availability of jobs for entry-level engineers. You will struggle hard to get your first job and be ready to spend more than a year in search
Build a solid portfolio, network to attract clients, and keep up with market changes. To achieve success, deliver high-quality work and communicate well.
To enter the job market in machine learning, it is essential to understand the fundamentals of artificial intelligence and models like GPT. There are 4-month courses and bootcamps that cover these concepts. To transition into machine learning operations roles, is it necessary to delve deeply into machine learning, or is a basic understanding sufficient to quickly move to projects involving generative AI and cloud-based machine learning operations? What projects can provide the most learning and attract recruiters' attention? Additionally, do you think the ability to reproduce and share results with data interpretation, using tools like Quarto with R and Python, will hold significant weight in the future? What machine learning projects would be most beneficial for a beginner to advance their learning and achieve employment or professional growth?
I was just about to message you on LinkedIn to express how much I love your content and to encourage you to keep creating video lectures on RU-vid. And then I saw your new video-perfect timing!👍
🎓 Start learning machine learning with the 'Introduction to Machine Learning with Python for Beginners' course, co-designed by me to give you practical, hands-on experience from day one. 🚀www.schoolofmachinelearning.com/introduction-to-machine-learning-with-python-for-beginners/
To be a successful freelance machine learning engineer, start by building a strong portfolio with diverse, high-impact projects that showcase your skills. Network actively to connect with potential clients and peers, and continually update your expertise to stay ahead in a rapidly evolving field. With Smythos, you'll gain access to cutting-edge resources and a supportive community to enhance your journey. With a blend of technical prowess, effective communication, and adaptability, you'll thrive in the freelance world and unlock exciting opportunities!
The fastest way to become a machine learning engineer is to combine focused learning with practical experience. Start with foundational courses on platforms like Coursera or edX, such as Andrew Ng’s Machine Learning course. Simultaneously, work on real-world projects and Kaggle competitions to build a strong portfolio. Networking with professionals and applying for internships will also accelerate your journey into the field.
Keep in mind that there is no such thing as an "entry level" ML engineer. You need massive ML experience for any ML role, nobody is trusting you with their data otherwise. Refer to "the data janitor" for more.
Some people are so poor all they have is money. Working on something that will ultimately be the end of human civilization really isn't something to brag about. But I understand, your love of money is all that brings you comfort in this world.
