On the occasion of WiE Day IEEE SIESGST started a series named WiE series, the inaugural episode of the WiE (Women in Engineering) series named “Breaking the Barriers “, marked a momentous occasion in celebrating the achievements and contributions of women in the field of engineering. The event, aimed to shed light on overcoming obstacles and empowering women to pursue careers in technical fields. With Ms. Usha Rengaraju, the world’s first women triple Kaggle Grandmaster, as the speaker. She shared her remarkable journey and expertise in the field of data science. Her specialization in Deep Learning and Probabilistic Graphical Models highlighted her dedication and passion for these areas. During the event, Ms. Rengaraju provided an overview of the key components of a machine learning algorithm, elucidating their contributions to the learning process. Understanding these components, such as data preprocessing, feature engineering, model selection, and evaluation, is crucial for building robust and accurate machine learning models. She discussed the impact of these technologies on the field, highlighting potential transformations expected in the industry in the coming years. The first episode was a resounding success in celebrating the achievements of women in engineering and promoting gender diversity in technical fields. The event served as a testament to the commitment of IEEE and WiE in empowering women and breaking the barriers in engineering. It paved the way for future episodes that will continue to inspire and empower women pursuing careers in technical fields. On the occasion of WiE Day IEEE SIESGST started a series named WiE series, the inaugural episode of the WiE (Women in Engineering) series named “Breaking the Barriers “, marked a momentous occasion in celebrating the achievements and contributions of women in the field of engineering. The event, aimed to shed light on overcoming obstacles and empowering women to pursue careers in technical fields. With Ms. Usha Rengaraju, the world’s first women triple Kaggle Grandmaster, as the speaker. She shared her remarkable journey and expertise in the field of data science. Her specialization in Deep Learning and Probabilistic Graphical Models highlighted her dedication and passion for these areas. During the event, Ms. Rengaraju provided an overview of the key components of a machine learning algorithm, elucidating their contributions to the learning process. Understanding these components, such as data preprocessing, feature engineering, model selection, and evaluation, is crucial for building robust and accurate machine learning models. She discussed the impact of these technologies on the field, highlighting potential transformations expected in the industry in the coming years. The first episode was a resounding success in celebrating the achievements of women in engineering and promoting gender diversity in technical fields. The event served as a testament to the commitment of IEEE and WiE in empowering women and breaking the barriers in engineering. It paved the way for future episodes that will continue to inspire and empower women pursuing careers in technical fields.