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Skills Covered in this Path
- Programming Concepts
- Python Basics
- Variables and Data types in Python
- Operators and Strings in Python
- Python Data Structures
- Control Flow Statements and Functions
- OOPs
- NumPy
- Pandas
- Perceptron
- ANN
- Gradient
- Backpropagation
- Activation Functions
- Softmax Function
- Python
- Statistics
- Reinforcement learning
- Machine learning
- TensorFlow library
- Deep Learning
- Neural Networks
- Artificial Intelligence
- Image Classification
- Tensors
- Python
- ANN
- Tensorflow
- Keras
- Gradient
- Backpropagation
- Reinforcement Learning
- States
- Actions
- State based mechanism in Reinforcement Learning
- Tokenization
- Stemming
- Lemmatization
- Removing Stopwords
- Modeling Techniques in NLP
- Machine Learning and Logistic Regression
- Sentiment Analysis
- Functionalities of Textblob
- Textblob Sentiment Analysis
- U-Net
- Semantic Segmentation
- Data Analysis
- SQL
- SQL with Python
- Triggers
- Big Data basics
- Hadoop
- HDFS
- Hive basics
- Hive querying
- Hive data upload
- Hive simple operations
- Spark
- RDDs
- Hadoop
- Hadoop
- Spark
- Real-time Data Analytics
- Spark streaming
- NoSQL
- MongoDB
- Basic Overview of MongoDB
- R Commands
- R Packages
- R Functions
- R Datatypes
- Operators in R
- RStudio
- HR Database Project
- DBMS
- RDBMS
- OpenCV
- Face Detection
- Face Recognition
- Deep Learning
- OpenCV Operations
- Face Detection demo
- Face Detection
- Face Recognition
- Applications of Face Recognition
- Face Detection using OpenCV using Python
