Machine Learning

Machine Learning is a subset of artificial intelligence that focuses on the development of algorithms and statistical models that enable computers to perform tasks without explicit instructions. It involves training models on data to make predictions or decisions based on patterns and trends in the data. Machine Learning is widely used in various applications, including image recognition, natural language processing, recommendation systems, and autonomous vehicles. It allows systems to learn from experience and improve their performance over time, making it a powerful tool for solving complex problems and automating processes.

Curriculum

Installation of Anaconda Prompt30:25🔒
Jupyter Notebook-An Overview25:40🔒
Shorcut Lkeys in Jupyter Notebook20:15🔒
Data Types in Python20:15🔒

Rules for Naming the Variables35:15🔒
List, Tuple, Set, Dictionary28:40🔒
"Introduction to Files and directories Introduction to the command prompt or terminal paths"22:30🔒
"Text files Reading from a text file Opening a file using `with`"18:25🔒

If, elif and else condition.30:25🔒
For and While Loop25:40🔒

Machine Learning Libraries30:25🔒
Numpy-Hands on25:40🔒

"Pandas-Hands on"45:30🔒

Learn how to explore, visualize, and extract insights from data42:30🔒
Data Visualization38:45🔒
Matplotlib-Hands on35:20🔒
Seaborn hands on28:15🔒

You need to think statistically and to speak the language of your data50:20🔒
Measures of Central Tendency35:45🔒
Measures of Dispersion42:30🔒
"IQR Statistics-Hands-On"42:30🔒

Classification, Regression, Fine-tuning your model50:20🔒
Supervised Learning35:45🔒
Unsupervised Learning35:45🔒
Linear Regression35:45🔒
"Metrics in Linear Regression Hands-on in Linear Regression35:45🔒

Logistic Regression50:20🔒
Metrics in Logistic Regression35:45🔒
Hands-on in Logistic Regression42:30🔒

Linear regression50:20🔒
Metrics for Linear regression35:45🔒

Introduction to Data Preprocessing50:20🔒
Standardizing Data35:45🔒
Exploratory Data Analysis42:30🔒
Missing Values42:30🔒
Outliers42:30🔒
"Standardization Mnormalization Feature Scaling and Selection42:30🔒

Decision Tree50:20🔒
Bagging35:45🔒
Boosting Random Forest42:30🔒

Neural Network50:20🔒

Learning Outcomes:

  • Upon Completing learners of Machine Learning acquire the ability to comprehend and articulate fundamental ML concepts, select and implement appropriate algorithms (using tools like Python), evaluate and optimize model performance, guard against biases such as overfitting, and apply ML techniques to solve real-world problems, including advanced topics like deep learning, reinforcement learning, and unsupervised learning.





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Price

₹3500

Course Title

Machine Learning

Language

English

Certification

Yes - Industry Recognized

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FAQs

The course duration is of 2 months & some course may extend to 3 months

Yes at the end of the course completion you will get certificates.

ABCPanda team will arrange a doubt clearance session accordingly.

Yes, for Recorded sessions & Live sessions access would be 1 year

No our mentors will teach from basic. If you have experience, it would add an advantage.