Complete Machine Learning With Real-World Deployment
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Interested in the field of Machine Learning? Then this course is perfect for you!
Designed by professional data scientists, this course offers a clear and engaging path to mastering complex machine-learning concepts, algorithms, and coding libraries.
Discover a comprehensive roadmap connecting key machine learning ideas, practical learning methods, and essential tools.
Machine learning has a real-world impact:
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Healthcare: Assisting in disease diagnosis and treatment recommendations.
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Transportation: Optimizing traffic flow with tools like Google Maps.
Python is the language of choice for data scientists. This course will guide you from Python basics to advanced deep learning techniques.
Uncover the world of AI through four key sections:
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Python: Build a strong foundation with data structures, libraries, and data preprocessing.
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Machine Learning: Master regression, classification, clustering, and NLP.
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Deep Learning: Explore neural networks, CNNs, RNNs, and more.
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Time Series Analysis: Gain insights from sequential data.
Learn by doing with hands-on exercises and real-world projects.
Who is this course for?
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Aspiring data scientists and machine learning enthusiasts
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Students seeking a career in data science
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Data analysts looking to advance their skills
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Anyone passionate about using data to drive business value
Join us on this exciting journey! I’m Akhil Vydyula, an Associate Consultant at Atos India specializing in data analytics and machine learning in the BFSI sector. With a passion for data-driven insights, I’m excited to share my knowledge and experience with you. Let’s explore the world of machine learning together!
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1Python Essentials: Exploring Data Structures and String OperationsVideo lesson
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2Python Mastery: Harnessing the Power of Lambda, Recursion, and FunctionsVideo lesson
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3Python for Data Analysis: Libraries, Exploratory Data Analysis, and DescriptiveVideo lesson
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4Python Interview Insights: Key Questions and StrategiesQuiz
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5Machine Learning Primer: Exploring Logistic Regression - A Classical AlgorithmsVideo lesson
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6Machine Learning Insights: Word Embedding Techniques - BoW, TF-IDF, Word2VecVideo lesson
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7Machine Learning Text Preprocessing: Cleaning and Preparing Amazon Reviews DataVideo lesson
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8Take Raw Data Set and Play with All the concepts you have learned in NLP ModuleText lesson
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9Machine Learning Fundamentals: Exploring Linear Regression - A Classical AlgoVideo lesson
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10Machine Learning Essentials: Understanding Decision Tree Classifier, RegressionVideo lesson
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11Machine Learning Insights: Geometric Intuition of Ensemble Models and FlaskVideo lesson
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12Machine Learning Data Analysis: Exploring Loan Approval Status with PredictiveVideo lesson
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13Machine Learning Unleashed: Unveiling K-means Clustering Techniques for UnsupervVideo lesson
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14Apply different number of epochs and try to decrease accuracy resultsText lesson
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15Deep Learning Foundations: Exploring Neural Networks, MLP, and BackpropagationVideo lesson
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16Deep Dive into Deep Learning:In-depth Understanding of RNN and LSTM with ExampleVideo lesson
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17Deep Learning Insights: Unveiling the Intuition Behind Computer Vision and CNNVideo lesson
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18Deep Learning Adventures: Mastering Convolutional Neural Networks with PizzaVideo lesson
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19Deep Learning Practical Guide: Transfer Learning with VGG16 Model & Hands-onVideo lesson
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20Deep Learning Web App: Building a Wild Animal Recognition System with CNNVideo lesson

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