Online or onsite, instructor-led live Sentiment Analysis (sometimes known as opinion mining or emotion AI) training courses demonstrate through interactive discussion and hands-on practice the fundamentals and advanced topics of Sentiment Analysis.
Sentiment Analysis training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Melbourne onsite live Sentiment Analysis trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
385 Bourke Street is located in the bustling Central Business District (CBD) and retail precinct of Melbourne's commercial hu...
385 Bourke Street is located in the bustling Central Business District (CBD) and retail precinct of Melbourne's commercial hub, making it by far the most sought after address in the City. Positioned directly opposite the Bourke street Mall, the 41 level tower houses a two level retail complex, known as the Galleria Retail Centre. Showcased underneath an impressive high glass ceiling, the retail specialty stores offer the best in giftware, fashion, food and services. The premium grade property is uniquely positioned on a 45 degree angle to the Melbourne CBD grid, providing excellent 360 degree views and has excellent access to public transport, with trams running along both Bourke and Elizabeth Streets and train and bus stations within 500 metres.
Cliftons Perth
Parmelia House, 191 St Georges Terrace, Perth, Australia, 6000
Located within the historic Bishops See precinct, it sits at the western end of Perth’s Commercial Business District
This instructor-led, live training in Melbourne (online or onsite) is aimed at intermediate-level data and marketing professionals who wish to apply LLMs to analyze and interpret public sentiment from various text sources such as social media posts, product reviews, and customer feedback.By the end of this training, participants will be able to:
Understand the principles of sentiment analysis and its application using LLMs.
Preprocess and prepare datasets for sentiment analysis.
Train and fine-tune LLMs to accurately reflect sentiment in text.
Analyze sentiment in real-time from social media and other text sources.
Integrate sentiment analysis findings into business strategies and decision-making processes.
This course has been designed for people interested in extracting meaning from written English text, though the knowledge can be applied to other human languages as well.
The course will cover how to make use of text written by humans, such as blog posts, tweets, etc...
For example, an analyst can set up an algorithm which will reach a conclusion automatically based on extensive data source.
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